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library_name: transformers
license: apache-2.0
base_model: c14kevincardenas/ClimBEiT-t3
tags:
- knowledge_distillation
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mobilevit-x-small_alpha0.7_temp3.0_t3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mobilevit-x-small_alpha0.7_temp3.0_t3
This model is a fine-tuned version of [c14kevincardenas/ClimBEiT-t3](https://huggingface.co/c14kevincardenas/ClimBEiT-t3) on the c14kevincardenas/beta_caller_284_person_crop_seq_withlimb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9598
- Accuracy: 0.6453
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5532 | 1.0 | 164 | 1.3950 | 0.2766 |
| 0.5286 | 2.0 | 328 | 1.3456 | 0.3015 |
| 0.4764 | 3.0 | 492 | 1.2156 | 0.4881 |
| 0.4397 | 4.0 | 656 | 1.1208 | 0.5499 |
| 0.4225 | 5.0 | 820 | 1.0595 | 0.5900 |
| 0.3976 | 6.0 | 984 | 1.0301 | 0.6085 |
| 0.3816 | 7.0 | 1148 | 1.0354 | 0.5987 |
| 0.3825 | 8.0 | 1312 | 1.0171 | 0.6182 |
| 0.3696 | 9.0 | 1476 | 0.9928 | 0.6269 |
| 0.3513 | 10.0 | 1640 | 1.0023 | 0.6226 |
| 0.3489 | 11.0 | 1804 | 1.0007 | 0.6095 |
| 0.3529 | 12.0 | 1968 | 0.9781 | 0.6377 |
| 0.3323 | 13.0 | 2132 | 0.9598 | 0.6453 |
| 0.3355 | 14.0 | 2296 | 0.9915 | 0.6388 |
| 0.3328 | 15.0 | 2460 | 0.9801 | 0.6377 |
| 0.3305 | 16.0 | 2624 | 0.9745 | 0.6388 |
| 0.3268 | 17.0 | 2788 | 0.9656 | 0.6497 |
| 0.3165 | 18.0 | 2952 | 0.9608 | 0.6529 |
| 0.3222 | 19.0 | 3116 | 0.9698 | 0.6421 |
| 0.3161 | 20.0 | 3280 | 0.9689 | 0.6421 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
|