README.md

---
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:120
- loss:MatryoshkaLoss
- loss:MultipleNegativesRankingLoss
base_model: Snowflake/snowflake-arctic-embed-l
widget:
- source_sentence: What muscles are primarily engaged during the described exercise
    sequence?
  sentences:
  - 'they stay even like you''ve got a spirit

    level from left to right hip

    stabilizing through your torso and your

    shoulder girdle by imprinting the

    shoulders back and down but lifting the

    pelvic floor and belly up pick your

    program here and then we''re going to put

    the headrest down we''re going into

    semicircle prep and reverse toes on the

    bar heels together so your feet are in a

    V position knees are hip bone width

    apart you''re going to tuck your tail

    under roll up press the carriage out

    roll down through the spine maintaining

    the carriage still and then return the

    carriage back into the stopper try and

    keep the carriage as close to the

    stopper as you can only push out sort of

    3/4 of the way so you can roll down and'
  - 'the silver Runner

    right foot is going mid-carriage

    hang those toes off to go right up

    against that edge and then coming up for

    that full lunge if that feels good and

    we''re lunging down hips are staying

    equal and then up and squeeze

    hips are definitely getting a little

    more tired on this side

    after everything that we''ve done

    lunge it down

    and squeeze it up

    good we''re moving so slow both ways

    inhale down

    exhale up

    we want to make sure our hips are equal

    front to back and side to side so kind

    of check that with your hands you may

    not have a mirror you can see

    so just kind of be aware of that

    it''s going to help us get the most out

    of this work

    spread through your toes on that

    standing leg

    you''re welcome to get a platform'
  - 'that back quad should be burning holding

    the carriage still to

    hold it on one we are actually going to

    reach down to the bar you''re gonna bring

    the back leg in shoot it all the way out

    straight

    from here hold it you''re gonna jump off

    of your right leg bring the carriage in

    and Pike up

    pulling the knee towards your chest

    and then place it back down so we''re

    gonna do one runner in shoot it out hold

    it there and then jump off Pike

    and place it back down

    so again run push it out jump off the

    right leg Pike place it down good run in

    exhale squeeze Pike it up

    and down and this is where we get that

    heart rate up

    and that quad really burning

    good so full body movement here

    shoulders

    chest

    are supporting big time in that Pike

    core is working'
- source_sentence: What modifications can be made to reduce wrist intensity during
    the exercise described?
  sentences:
  - 'forward

    Bend and extend good bicep

    good if you need extra support for that

    standing wrist you can place that knee

    down you can even come here

    yeah lots of options

    see I''m on like the fingertips or ball

    of my hand I know that can be intense

    for your wrist

    keep it up

    [Applause]

    and two

    whoo

    hold it out on one

    hold it hold it lower and lift the leg

    just five

    core is tight for

    three

    two

    and a one and bring it in

    that is intense all right we''re gonna

    roll all the way up

    onto your knees core is nice and tight

    we''re gonna bring that arm forward turn

    the Palm down

    and I''m going to rotate

    and then punch

    really really using those obliques

    keeping the hips Square

    opening through the chest

    think about both obliques helping you

    on that rotation back'
  - 'neck too

    and one

    good we''re going to pull our arms down

    by our sides hold it down there

    tricep press keeping the elbows tight

    and reach

    just two more this way

    then we''re going to be doing like an L

    with our tricep so open your right

    tricep out to the side left tricep

    towards the ceiling and then come back

    to center now open the left tricep out

    to the side right tricep up towards the

    ceiling and down

    good

    meanwhile you''re keeping your shoulders

    nice and stable

    inhale and exhale through it inhale to

    bend exhale to straighten if you feel

    that low back

    Bend those knees in closer

    last

    set

    of each side one squeeze

    one

    squeeze find your Center and release

    good

    open those arms out to the side and rock

    your knees over to one side for a little'
  - 'heels on the bar hip distance there we

    go inhale

    exhale we''re just going to tuck into our

    imprint

    pressing that low back down activating

    the core and inhale Rock back

    and exhale press that low back down

    going into your imprinted spine and then

    rocking back to your neutral

    good keep that breathing going we''re

    thinking just ribs towards your hips as

    you rock into that imprint and then Rock

    back

    one more time

    and rock it back this time we''re going

    to roll all the way up press that low

    back down and then scoop the hips use

    the hamstrings and glutes to roll up we

    want to keep the carriage into the

    stopper that''s the challenging part

    inhale and then exhale soften from the

    ribs and roll back down one vertebrae at'
- source_sentence: How does Dez suggest protecting the neck during the hip rolls exercise?
  sentences:
  - 'apart

    make sure you''re back in your neutral

    spine we''re going to go into a hip lift

    so that means you''re only lifting your

    hips

    one or two inches off the carriage

    everything stays the same

    natural curve of the low back tiny hover

    here you''re going to reach the carriage

    out keeping those hips in the same

    position and then bring it back in

    again inhale out

    exhale think about activating the core

    that deep transverse muscle to help pull

    the carriage in

    good we''re also still working from the

    hamstrings and glutes

    keeping your feet stable in one place

    if the low back is firing just lower

    your hips back down on the carriage and

    continue to press that way

    last three exhale Pull It in nice and

    slow and controlled squeeze at the top'
  - '[Music]

    foreign

    [Music]

    hey guys welcome back to my channel I''m

    Dez and today I''m taking you through

    another full body Pilates reformer

    workout this workout includes some fun

    and challenging series and will give you

    a full class experience you won''t need

    any additional props today just you and

    your reformer so let''s get started

    okay you guys we''re going to start today

    on two heavy Springs with hip rolls so

    if you need additional assistance for

    your low back add on also a light to

    medium tension spring I''m going to be

    going to two heavy Springs or two Reds

    on this machine

    and we''re going to light on on our box

    head rest will be down flat

    to protect the neck

    good we''re going to place our heels on

    the bar

    find your neutral spine'
  - 'lower back and now we''re doing heel Jake

    the peg so the heels in line with the

    sit bone the other leg is up towards the

    ceiling or there abouts you lower down

    and then return now imagine the inside

    thighs almost glued together they''re

    moving as one unit this is a pelvic

    stability exercise so you want to be

    able to do this movement in the legs

    without rocking tucking the pelvis or

    the lower back the tail bones down is a

    little hollow in the lower back and then

    heel in line with the sit bone other leg

    up energy out through the legs breathing

    out through the mouth and then in

    through the nose out through the mouth

    and then in through the nose may want to

    place the hands on the hips of the bones

    of the pelvis there making sure that'
- source_sentence: What specific movements are suggested to engage the core during
    the exercise described?
  sentences:
  - 'balance and control

    if it''s too much having that leg lifted

    just drop your knee back down

    all right we''re gonna add it on here

    lift in those ribs we''re going to bend

    the elbow then we''re gonna punch it

    forward

    bend it and extend behind you oh good

    you guys Bend

    use that core extend forward

    and return

    and Ben

    big exhale forward

    and back check those hips that they''re

    equal you''re not sinking

    to one side

    three more

    use that belly you guys

    if you''re fill in the back just place

    that knee down two

    all right hold it up there on one use

    the belly use the core hold hold hold

    drop the leg and lift just five squeeze

    the booty four

    three

    two

    and one and bring it in

    give yourself a little round through

    your back

    all right we''re staying in this kneeling'
  - 'slow it down go for it but you are

    trying to get a little bit about heart

    rate jump here

    good

    three more

    squeeze Pike and lift use that belly

    button

    and two

    last one

    and lift

    good you guys all right crossing your

    left foot in front of your right now

    staying soft through your left knee

    Pike it up kind of tucking through your

    tailbone relax the shoulders then we''re

    gonna roll through your spine

    all the way

    to a flat back rolling those shoulders

    down and then you''re going to tuck your

    chin and Pike it up again trying not to

    Pike with your shoulders up in your ears

    roll it back down

    head comes up last good and then tuck

    your chin roll it up good

    roll through

    tucking from the glutes

    rolling through your spine sliding that'
  - 'easy to want to like sway if you want to

    take a look at my back this is what we

    don''t want yeah we want to be lifted and

    zipped through the rib cage

    as we continue that bicep curl

    stay soft through your right elbow

    I know easier said than done we have a

    lot that we''re supporting through that

    right arm now

    two

    and one we''re gonna now reach the right

    leg back

    keep everything Square continue that

    bicep curl

    and it''s normal to feel very unstable

    and you might notice that this side

    feels harder than the other side or vice

    versa maybe this is your more dominant

    side for balance

    oh

    I''m feeling it

    slide my hand over a little bit

    all right try not to let that leg sink

    down

    but drop that knee if you need it we''re

    going to add on bicep curl punch it'
- source_sentence: What modifications are suggested if the exercise feels too intense
    on the arms or wrists?
  sentences:
  - 'towards the spine but keep the spine in

    a neutral position fully straighten the

    legs when you straighten them and now

    into VMO knock-knees okay so your toes

    are exactly where they are you push out

    keeping the knees together go all the

    way back into the stopper and then

    within that range you''re going to do 20

    of these so the knees are together

    throughout the whole of the exercise the

    toes are on the bar as they were in the

    V position but then the heels are out

    wider so it''s like a knocked knee this

    really gets into the muscles on the

    inside of the knees and the inside of

    the legs in through the nose out through

    the mouth

    expanding the ribs and then contracting

    the abdominals keeping the muscles in

    the legs engaged throughout prehensile'
  - 'are done

    thank you so much for joining me today

    that had some intense moments I know I

    hope that it felt good this was a

    definitely like a full class workout I

    hope that you guys enjoyed it and if you

    did please hit that like button make

    sure you''re subscribed to my channel and

    follow me on Instagram for more fun and

    workout content and I hope to see you

    next time thank you so much'
  - 'spine relax the shoulders lift the head

    and again

    head goes down Pike it up inhale

    and exhale roll through

    [Applause]

    good keep going here if this is too

    intense on the arms or wrists especially

    you''re going to do the same thing here

    Pike it up

    on your knees and roll through my knees

    are just kind of facing over to the left

    side Pike it up

    inhale and exhale roll

    good two more you guys you''re doing so

    good it''s intense I know

    roll through

    and lift

    last one

    and finishing that Pike good you guys

    take those feet

    onto the carriage catch your breath if

    you want lean it back if you can lift

    your foot bar to find that click to kind

    of lean back stretch through your

    shoulders kind of depending on your

    reformer if yours is able to pull back'
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics:
- cosine_accuracy@1
- cosine_accuracy@3
- cosine_accuracy@5
- cosine_accuracy@10
- cosine_precision@1
- cosine_precision@3
- cosine_precision@5
- cosine_precision@10
- cosine_recall@1
- cosine_recall@3
- cosine_recall@5
- cosine_recall@10
- cosine_ndcg@10
- cosine_mrr@10
- cosine_map@100
model-index:
- name: SentenceTransformer based on Snowflake/snowflake-arctic-embed-l
  results:
  - task:
      type: information-retrieval
      name: Information Retrieval
    dataset:
      name: Unknown
      type: unknown
    metrics:
    - type: cosine_accuracy@1
      value: 0.7333333333333333
      name: Cosine Accuracy@1
    - type: cosine_accuracy@3
      value: 0.9666666666666667
      name: Cosine Accuracy@3
    - type: cosine_accuracy@5
      value: 1.0
      name: Cosine Accuracy@5
    - type: cosine_accuracy@10
      value: 1.0
      name: Cosine Accuracy@10
    - type: cosine_precision@1
      value: 0.7333333333333333
      name: Cosine Precision@1
    - type: cosine_precision@3
      value: 0.32222222222222224
      name: Cosine Precision@3
    - type: cosine_precision@5
      value: 0.20000000000000007
      name: Cosine Precision@5
    - type: cosine_precision@10
      value: 0.10000000000000003
      name: Cosine Precision@10
    - type: cosine_recall@1
      value: 0.7333333333333333
      name: Cosine Recall@1
    - type: cosine_recall@3
      value: 0.9666666666666667
      name: Cosine Recall@3
    - type: cosine_recall@5
      value: 1.0
      name: Cosine Recall@5
    - type: cosine_recall@10
      value: 1.0
      name: Cosine Recall@10
    - type: cosine_ndcg@10
      value: 0.8759880689316304
      name: Cosine Ndcg@10
    - type: cosine_mrr@10
      value: 0.8344444444444444
      name: Cosine Mrr@10
    - type: cosine_map@100
      value: 0.8344444444444444
      name: Cosine Map@100
---

# SentenceTransformer based on Snowflake/snowflake-arctic-embed-l

This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [Snowflake/snowflake-arctic-embed-l](https://huggingface.co/Snowflake/snowflake-arctic-embed-l). It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.

## Model Details

### Model Description
- **Model Type:** Sentence Transformer
- **Base model:** [Snowflake/snowflake-arctic-embed-l](https://huggingface.co/Snowflake/snowflake-arctic-embed-l) <!-- at revision d8fb21ca8d905d2832ee8b96c894d3298964346b -->
- **Maximum Sequence Length:** 512 tokens
- **Output Dimensionality:** 1024 dimensions
- **Similarity Function:** Cosine Similarity
<!-- - **Training Dataset:** Unknown -->
<!-- - **Language:** Unknown -->
<!-- - **License:** Unknown -->

### Model Sources

- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)

### Full Model Architecture

```
SentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
  (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
  (2): Normalize()
)
```

## Usage

### Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

```bash
pip install -U sentence-transformers
```

Then you can load this model and run inference.
```python
from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("AneetaXavier/reformer-pilates-embed-ft-49fc1835-9968-433d-9c45-1538ea91dcc9")
# Run inference
sentences = [
    'What modifications are suggested if the exercise feels too intense on the arms or wrists?',
    "spine relax the shoulders lift the head\nand again\nhead goes down Pike it up inhale\nand exhale roll through\n[Applause]\ngood keep going here if this is too\nintense on the arms or wrists especially\nyou're going to do the same thing here\nPike it up\non your knees and roll through my knees\nare just kind of facing over to the left\nside Pike it up\ninhale and exhale roll\ngood two more you guys you're doing so\ngood it's intense I know\nroll through\nand lift\nlast one\nand finishing that Pike good you guys\ntake those feet\nonto the carriage catch your breath if\nyou want lean it back if you can lift\nyour foot bar to find that click to kind\nof lean back stretch through your\nshoulders kind of depending on your\nreformer if yours is able to pull back",
    "towards the spine but keep the spine in\na neutral position fully straighten the\nlegs when you straighten them and now\ninto VMO knock-knees okay so your toes\nare exactly where they are you push out\nkeeping the knees together go all the\nway back into the stopper and then\nwithin that range you're going to do 20\nof these so the knees are together\nthroughout the whole of the exercise the\ntoes are on the bar as they were in the\nV position but then the heels are out\nwider so it's like a knocked knee this\nreally gets into the muscles on the\ninside of the knees and the inside of\nthe legs in through the nose out through\nthe mouth\nexpanding the ribs and then contracting\nthe abdominals keeping the muscles in\nthe legs engaged throughout prehensile",
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 1024]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]
```

<!--
### Direct Usage (Transformers)

<details><summary>Click to see the direct usage in Transformers</summary>

</details>
-->

<!--
### Downstream Usage (Sentence Transformers)

You can finetune this model on your own dataset.

<details><summary>Click to expand</summary>

</details>
-->

<!--
### Out-of-Scope Use

*List how the model may foreseeably be misused and address what users ought not to do with the model.*
-->

## Evaluation

### Metrics

#### Information Retrieval

* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)

| Metric              | Value     |
|:--------------------|:----------|
| cosine_accuracy@1   | 0.7333    |
| cosine_accuracy@3   | 0.9667    |
| cosine_accuracy@5   | 1.0       |
| cosine_accuracy@10  | 1.0       |
| cosine_precision@1  | 0.7333    |
| cosine_precision@3  | 0.3222    |
| cosine_precision@5  | 0.2       |
| cosine_precision@10 | 0.1       |
| cosine_recall@1     | 0.7333    |
| cosine_recall@3     | 0.9667    |
| cosine_recall@5     | 1.0       |
| cosine_recall@10    | 1.0       |
| **cosine_ndcg@10**  | **0.876** |
| cosine_mrr@10       | 0.8344    |
| cosine_map@100      | 0.8344    |

<!--
## Bias, Risks and Limitations

*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
-->

<!--
### Recommendations

*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
-->

## Training Details

### Training Dataset

#### Unnamed Dataset

* Size: 120 training samples
* Columns: <code>sentence_0</code> and <code>sentence_1</code>
* Approximate statistics based on the first 120 samples:
  |         | sentence_0                                                                         | sentence_1                                                                           |
  |:--------|:-----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
  | type    | string                                                                             | string                                                                               |
  | details | <ul><li>min: 12 tokens</li><li>mean: 18.46 tokens</li><li>max: 29 tokens</li></ul> | <ul><li>min: 85 tokens</li><li>mean: 158.07 tokens</li><li>max: 173 tokens</li></ul> |
* Samples:
  | sentence_0                                                                                                             | sentence_1                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
  |:-----------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
  | <code>What equipment and spring settings does Dez recommend for starting the Pilates reformer workout?</code>          | <code>[Music]<br>foreign<br>[Music]<br>hey guys welcome back to my channel I'm<br>Dez and today I'm taking you through<br>another full body Pilates reformer<br>workout this workout includes some fun<br>and challenging series and will give you<br>a full class experience you won't need<br>any additional props today just you and<br>your reformer so let's get started<br>okay you guys we're going to start today<br>on two heavy Springs with hip rolls so<br>if you need additional assistance for<br>your low back add on also a light to<br>medium tension spring I'm going to be<br>going to two heavy Springs or two Reds<br>on this machine<br>and we're going to light on on our box<br>head rest will be down flat<br>to protect the neck<br>good we're going to place our heels on<br>the bar<br>find your neutral spine</code> |
  | <code>How does Dez suggest protecting the neck during the hip rolls exercise?</code>                                   | <code>[Music]<br>foreign<br>[Music]<br>hey guys welcome back to my channel I'm<br>Dez and today I'm taking you through<br>another full body Pilates reformer<br>workout this workout includes some fun<br>and challenging series and will give you<br>a full class experience you won't need<br>any additional props today just you and<br>your reformer so let's get started<br>okay you guys we're going to start today<br>on two heavy Springs with hip rolls so<br>if you need additional assistance for<br>your low back add on also a light to<br>medium tension spring I'm going to be<br>going to two heavy Springs or two Reds<br>on this machine<br>and we're going to light on on our box<br>head rest will be down flat<br>to protect the neck<br>good we're going to place our heels on<br>the bar<br>find your neutral spine</code> |
  | <code>What is the correct breathing technique to use while rocking between imprint and neutral spine positions?</code> | <code>heels on the bar hip distance there we<br>go inhale<br>exhale we're just going to tuck into our<br>imprint<br>pressing that low back down activating<br>the core and inhale Rock back<br>and exhale press that low back down<br>going into your imprinted spine and then<br>rocking back to your neutral<br>good keep that breathing going we're<br>thinking just ribs towards your hips as<br>you rock into that imprint and then Rock<br>back<br>one more time<br>and rock it back this time we're going<br>to roll all the way up press that low<br>back down and then scoop the hips use<br>the hamstrings and glutes to roll up we<br>want to keep the carriage into the<br>stopper that's the challenging part<br>inhale and then exhale soften from the<br>ribs and roll back down one vertebrae at</code>                           |
* Loss: [<code>MatryoshkaLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#matryoshkaloss) with these parameters:
  ```json
  {
      "loss": "MultipleNegativesRankingLoss",
      "matryoshka_dims": [
          768,
          512,
          256,
          128,
          64
      ],
      "matryoshka_weights": [
          1,
          1,
          1,
          1,
          1
      ],
      "n_dims_per_step": -1
  }
  ```

### Training Hyperparameters
#### Non-Default Hyperparameters

- `eval_strategy`: steps
- `per_device_train_batch_size`: 10
- `per_device_eval_batch_size`: 10
- `num_train_epochs`: 30
- `multi_dataset_batch_sampler`: round_robin

#### All Hyperparameters
<details><summary>Click to expand</summary>

- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: steps
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 10
- `per_device_eval_batch_size`: 10
- `per_gpu_train_batch_size`: None
- `per_gpu_eval_batch_size`: None
- `gradient_accumulation_steps`: 1
- `eval_accumulation_steps`: None
- `torch_empty_cache_steps`: None
- `learning_rate`: 5e-05
- `weight_decay`: 0.0
- `adam_beta1`: 0.9
- `adam_beta2`: 0.999
- `adam_epsilon`: 1e-08
- `max_grad_norm`: 1
- `num_train_epochs`: 30
- `max_steps`: -1
- `lr_scheduler_type`: linear
- `lr_scheduler_kwargs`: {}
- `warmup_ratio`: 0.0
- `warmup_steps`: 0
- `log_level`: passive
- `log_level_replica`: warning
- `log_on_each_node`: True
- `logging_nan_inf_filter`: True
- `save_safetensors`: True
- `save_on_each_node`: False
- `save_only_model`: False
- `restore_callback_states_from_checkpoint`: False
- `no_cuda`: False
- `use_cpu`: False
- `use_mps_device`: False
- `seed`: 42
- `data_seed`: None
- `jit_mode_eval`: False
- `use_ipex`: False
- `bf16`: False
- `fp16`: False
- `fp16_opt_level`: O1
- `half_precision_backend`: auto
- `bf16_full_eval`: False
- `fp16_full_eval`: False
- `tf32`: None
- `local_rank`: 0
- `ddp_backend`: None
- `tpu_num_cores`: None
- `tpu_metrics_debug`: False
- `debug`: []
- `dataloader_drop_last`: False
- `dataloader_num_workers`: 0
- `dataloader_prefetch_factor`: None
- `past_index`: -1
- `disable_tqdm`: False
- `remove_unused_columns`: True
- `label_names`: None
- `load_best_model_at_end`: False
- `ignore_data_skip`: False
- `fsdp`: []
- `fsdp_min_num_params`: 0
- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
- `tp_size`: 0
- `fsdp_transformer_layer_cls_to_wrap`: None
- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
- `deepspeed`: None
- `label_smoothing_factor`: 0.0
- `optim`: adamw_torch
- `optim_args`: None
- `adafactor`: False
- `group_by_length`: False
- `length_column_name`: length
- `ddp_find_unused_parameters`: None
- `ddp_bucket_cap_mb`: None
- `ddp_broadcast_buffers`: False
- `dataloader_pin_memory`: True
- `dataloader_persistent_workers`: False
- `skip_memory_metrics`: True
- `use_legacy_prediction_loop`: False
- `push_to_hub`: False
- `resume_from_checkpoint`: None
- `hub_model_id`: None
- `hub_strategy`: every_save
- `hub_private_repo`: None
- `hub_always_push`: False
- `gradient_checkpointing`: False
- `gradient_checkpointing_kwargs`: None
- `include_inputs_for_metrics`: False
- `include_for_metrics`: []
- `eval_do_concat_batches`: True
- `fp16_backend`: auto
- `push_to_hub_model_id`: None
- `push_to_hub_organization`: None
- `mp_parameters`: 
- `auto_find_batch_size`: False
- `full_determinism`: False
- `torchdynamo`: None
- `ray_scope`: last
- `ddp_timeout`: 1800
- `torch_compile`: False
- `torch_compile_backend`: None
- `torch_compile_mode`: None
- `include_tokens_per_second`: False
- `include_num_input_tokens_seen`: False
- `neftune_noise_alpha`: None
- `optim_target_modules`: None
- `batch_eval_metrics`: False
- `eval_on_start`: False
- `use_liger_kernel`: False
- `eval_use_gather_object`: False
- `average_tokens_across_devices`: False
- `prompts`: None
- `batch_sampler`: batch_sampler
- `multi_dataset_batch_sampler`: round_robin

</details>

### Training Logs
| Epoch   | Step | cosine_ndcg@10 |
|:-------:|:----:|:--------------:|
| 1.0     | 12   | 0.8455         |
| 2.0     | 24   | 0.8970         |
| 3.0     | 36   | 0.9064         |
| 4.0     | 48   | 0.9237         |
| 4.1667  | 50   | 0.9360         |
| 5.0     | 60   | 0.8633         |
| 6.0     | 72   | 0.9016         |
| 7.0     | 84   | 0.8814         |
| 8.0     | 96   | 0.8676         |
| 8.3333  | 100  | 0.8599         |
| 9.0     | 108  | 0.8633         |
| 10.0    | 120  | 0.8903         |
| 11.0    | 132  | 0.8760         |
| 12.0    | 144  | 0.8793         |
| 12.5    | 150  | 0.8960         |
| 13.0    | 156  | 0.8970         |
| 14.0    | 168  | 0.8970         |
| 15.0    | 180  | 0.9026         |
| 16.0    | 192  | 0.8903         |
| 16.6667 | 200  | 0.8804         |
| 17.0    | 204  | 0.8927         |
| 18.0    | 216  | 0.9093         |
| 19.0    | 228  | 0.8960         |
| 20.0    | 240  | 0.8916         |
| 20.8333 | 250  | 0.8916         |
| 21.0    | 252  | 0.8916         |
| 22.0    | 264  | 0.8927         |
| 23.0    | 276  | 0.8916         |
| 24.0    | 288  | 0.8916         |
| 25.0    | 300  | 0.8750         |
| 26.0    | 312  | 0.8750         |
| 27.0    | 324  | 0.8627         |
| 28.0    | 336  | 0.8637         |
| 29.0    | 348  | 0.8760         |
| 29.1667 | 350  | 0.8760         |
| 30.0    | 360  | 0.8760         |


### Framework Versions
- Python: 3.11.12
- Sentence Transformers: 4.1.0
- Transformers: 4.51.3
- PyTorch: 2.6.0+cu124
- Accelerate: 1.6.0
- Datasets: 2.14.4
- Tokenizers: 0.21.1

## Citation

### BibTeX

#### Sentence Transformers
```bibtex
@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}
```

#### MatryoshkaLoss
```bibtex
@misc{kusupati2024matryoshka,
    title={Matryoshka Representation Learning},
    author={Aditya Kusupati and Gantavya Bhatt and Aniket Rege and Matthew Wallingford and Aditya Sinha and Vivek Ramanujan and William Howard-Snyder and Kaifeng Chen and Sham Kakade and Prateek Jain and Ali Farhadi},
    year={2024},
    eprint={2205.13147},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}
```

#### MultipleNegativesRankingLoss
```bibtex
@misc{henderson2017efficient,
    title={Efficient Natural Language Response Suggestion for Smart Reply},
    author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
    year={2017},
    eprint={1705.00652},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}
```

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