HimashaJ96
/

zephyr-Me

@@ -1,204 +1,114 @@
 ---
-library_name: peft
 base_model: TheBloke/zephyr-7B-beta-GPTQ
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-### Model Sources [optional]
-<!-- Provide the basic links for the model. -->
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-## Uses
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-### Direct Use
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-[More Information Needed]
-### Downstream Use [optional]
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-[More Information Needed]
-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-[More Information Needed]
-## Bias, Risks, and Limitations
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-[More Information Needed]
-### Recommendations
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-## How to Get Started with the Model
-Use the code below to get started with the model.
-[More Information Needed]
-## Training Details
-### Training Data
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-[More Information Needed]
-### Training Procedure
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-#### Preprocessing [optional]
-[More Information Needed]
-#### Training Hyperparameters
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-#### Speeds, Sizes, Times [optional]
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-[More Information Needed]
-## Evaluation
-<!-- This section describes the evaluation protocols and provides the results. -->
-### Testing Data, Factors & Metrics
-#### Testing Data
-<!-- This should link to a Dataset Card if possible. -->
-[More Information Needed]
-#### Factors
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-[More Information Needed]
-#### Metrics
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-[More Information Needed]
-### Results
-[More Information Needed]
-#### Summary
-## Model Examination [optional]
-<!-- Relevant interpretability work for the model goes here -->
-[More Information Needed]
-## Environmental Impact
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-## Technical Specifications [optional]
-### Model Architecture and Objective
-[More Information Needed]
-### Compute Infrastructure
-[More Information Needed]
-#### Hardware
-[More Information Needed]
-#### Software
-[More Information Needed]
-## Citation [optional]
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-**BibTeX:**
-[More Information Needed]
-**APA:**
-[More Information Needed]
-## Glossary [optional]
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-[More Information Needed]
-## More Information [optional]
-[More Information Needed]
-## Model Card Authors [optional]
-[More Information Needed]
-## Model Card Contact
-[More Information Needed]
 ### Framework versions
-- PEFT 0.7.1

 ---
+license: mit
 base_model: TheBloke/zephyr-7B-beta-GPTQ
+tags:
+- trl
+- sft
+- generated_from_trainer
+metrics:
+- rouge
+model-index:
+- name: zephyr-Me
+  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. -->
+# zephyr-Me
+This model is a fine-tuned version of [TheBloke/zephyr-7B-beta-GPTQ](https://huggingface.co/TheBloke/zephyr-7B-beta-GPTQ) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1902
+- Rouge1: 0.7317
+- Rouge2: 0.5171
+- Rougel: 0.6950
+- Rougelsum: 0.7186
+- Meteor: 0.7271
+- F1 Score: 0.0012
+## 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: 0.0002
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 7
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Meteor | F1 Score |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:------:|:--------:|
+| 2.1246        | 0.15  | 4    | 2.0611          | 0.5115 | 0.1858 | 0.4164 | 0.4770    | 0.4928 | 0.0077   |
+| 1.6866        | 0.3   | 8    | 1.5126          | 0.6085 | 0.3404 | 0.5486 | 0.5946    | 0.5857 | 0.0010   |
+| 1.3126        | 0.44  | 12   | 1.3238          | 0.6578 | 0.4124 | 0.6046 | 0.6364    | 0.6452 | 0.0010   |
+| 1.1583        | 0.59  | 16   | 1.2688          | 0.6662 | 0.4166 | 0.6126 | 0.6434    | 0.6477 | 0.0008   |
+| 1.1011        | 0.74  | 20   | 1.1857          | 0.6776 | 0.4200 | 0.6254 | 0.6559    | 0.6568 | 0.0008   |
+| 1.0343        | 0.89  | 24   | 1.1439          | 0.6730 | 0.4174 | 0.6238 | 0.6512    | 0.6587 | 0.0008   |
+| 1.0673        | 1.04  | 28   | 1.1088          | 0.6922 | 0.4335 | 0.6360 | 0.6684    | 0.6753 | 0.0008   |
+| 0.8681        | 1.19  | 32   | 1.1131          | 0.6992 | 0.4523 | 0.6488 | 0.6769    | 0.6862 | 0.0010   |
+| 0.8605        | 1.33  | 36   | 1.0888          | 0.7064 | 0.4606 | 0.6585 | 0.6873    | 0.6958 | 0.0010   |
+| 0.8603        | 1.48  | 40   | 1.0543          | 0.7074 | 0.4638 | 0.6582 | 0.6869    | 0.6894 | 0.0010   |
+| 0.8354        | 1.63  | 44   | 1.0298          | 0.7050 | 0.4631 | 0.6586 | 0.6856    | 0.6840 | 0.0010   |
+| 0.7906        | 1.78  | 48   | 1.0037          | 0.7084 | 0.4712 | 0.6642 | 0.6902    | 0.6887 | 0.0010   |
+| 0.7108        | 1.93  | 52   | 0.9887          | 0.7113 | 0.4766 | 0.6658 | 0.6920    | 0.7017 | 0.0010   |
+| 0.7009        | 2.07  | 56   | 0.9943          | 0.7109 | 0.4787 | 0.6679 | 0.6925    | 0.7025 | 0.0010   |
+| 0.5753        | 2.22  | 60   | 0.9924          | 0.7235 | 0.4846 | 0.6741 | 0.7042    | 0.7064 | 0.0012   |
+| 0.5952        | 2.37  | 64   | 0.9602          | 0.7219 | 0.4928 | 0.6818 | 0.7066    | 0.7135 | 0.0010   |
+| 0.5637        | 2.52  | 68   | 0.9766          | 0.7168 | 0.4924 | 0.6807 | 0.7011    | 0.7109 | 0.0010   |
+| 0.5426        | 2.67  | 72   | 0.9713          | 0.7218 | 0.4944 | 0.6823 | 0.7065    | 0.7094 | 0.0010   |
+| 0.5503        | 2.81  | 76   | 0.9860          | 0.7183 | 0.4937 | 0.6805 | 0.7049    | 0.7118 | 0.0010   |
+| 0.4929        | 2.96  | 80   | 0.9701          | 0.7229 | 0.4987 | 0.6849 | 0.7076    | 0.7196 | 0.0010   |
+| 0.4505        | 3.11  | 84   | 0.9851          | 0.7209 | 0.5006 | 0.6871 | 0.7085    | 0.7173 | 0.0010   |
+| 0.4012        | 3.26  | 88   | 1.0122          | 0.7267 | 0.5080 | 0.6914 | 0.7115    | 0.7264 | 0.0010   |
+| 0.3709        | 3.41  | 92   | 0.9842          | 0.7326 | 0.5125 | 0.6941 | 0.7162    | 0.7294 | 0.0010   |
+| 0.3962        | 3.56  | 96   | 1.0035          | 0.7337 | 0.5154 | 0.6972 | 0.7201    | 0.7293 | 0.0010   |
+| 0.4           | 3.7   | 100  | 1.0013          | 0.7306 | 0.5143 | 0.6951 | 0.7179    | 0.7318 | 0.0010   |
+| 0.3689        | 3.85  | 104  | 0.9994          | 0.7315 | 0.5113 | 0.6936 | 0.7180    | 0.7294 | 0.0010   |
+| 0.3805        | 4.0   | 108  | 1.0023          | 0.7418 | 0.5219 | 0.7029 | 0.7279    | 0.7353 | 0.0010   |
+| 0.3162        | 4.15  | 112  | 1.0605          | 0.7406 | 0.5222 | 0.7023 | 0.7250    | 0.7380 | 0.0010   |
+| 0.2983        | 4.3   | 116  | 1.0506          | 0.7410 | 0.5240 | 0.7042 | 0.7272    | 0.7370 | 0.0010   |
+| 0.2766        | 4.44  | 120  | 1.0229          | 0.7384 | 0.5199 | 0.7048 | 0.7249    | 0.7361 | 0.0010   |
+| 0.2413        | 4.59  | 124  | 1.0696          | 0.7372 | 0.5198 | 0.7044 | 0.7251    | 0.7366 | 0.0010   |
+| 0.268         | 4.74  | 128  | 1.0809          | 0.7351 | 0.5153 | 0.6998 | 0.7222    | 0.7320 | 0.0010   |
+| 0.2555        | 4.89  | 132  | 1.0408          | 0.7357 | 0.5211 | 0.7011 | 0.7215    | 0.7332 | 0.0010   |
+| 0.2579        | 5.04  | 136  | 1.0279          | 0.7361 | 0.5178 | 0.6986 | 0.7215    | 0.7324 | 0.0010   |
+| 0.2071        | 5.19  | 140  | 1.0943          | 0.7380 | 0.5186 | 0.7001 | 0.7240    | 0.7357 | 0.0012   |
+| 0.2076        | 5.33  | 144  | 1.1801          | 0.7342 | 0.5154 | 0.6983 | 0.7220    | 0.7275 | 0.0012   |
+| 0.2211        | 5.48  | 148  | 1.1742          | 0.7334 | 0.5144 | 0.6960 | 0.7197    | 0.7273 | 0.0012   |
+| 0.1828        | 5.63  | 152  | 1.1487          | 0.7350 | 0.5180 | 0.6981 | 0.7213    | 0.7301 | 0.0012   |
+| 0.2016        | 5.78  | 156  | 1.1384          | 0.7373 | 0.5195 | 0.7000 | 0.7234    | 0.7314 | 0.0012   |
+| 0.2279        | 5.93  | 160  | 1.1391          | 0.7390 | 0.5228 | 0.7021 | 0.7252    | 0.7332 | 0.0012   |
+| 0.2045        | 6.07  | 164  | 1.1427          | 0.7378 | 0.5208 | 0.7014 | 0.7246    | 0.7323 | 0.0012   |
+| 0.1642        | 6.22  | 168  | 1.1598          | 0.7357 | 0.5188 | 0.6996 | 0.7227    | 0.7310 | 0.0012   |
+| 0.1858        | 6.37  | 172  | 1.1764          | 0.7341 | 0.5183 | 0.6980 | 0.7211    | 0.7288 | 0.0012   |
+| 0.1869        | 6.52  | 176  | 1.1846          | 0.7317 | 0.5162 | 0.6954 | 0.7184    | 0.7269 | 0.0012   |
+| 0.1754        | 6.67  | 180  | 1.1886          | 0.7324 | 0.5175 | 0.6955 | 0.7192    | 0.7273 | 0.0012   |
+| 0.1634        | 6.81  | 184  | 1.1898          | 0.7317 | 0.5171 | 0.6950 | 0.7186    | 0.7271 | 0.0012   |
+| 0.1853        | 6.96  | 188  | 1.1902          | 0.7317 | 0.5171 | 0.6950 | 0.7186    | 0.7271 | 0.0012   |
 ### Framework versions
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.0
+- Tokenizers 0.15.0

adapter_model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2a77d80859cfd8537773e3138c4805b951e3dccbc7e59abf5d026619e6baeeb6
 size 109086416

 version https://git-lfs.github.com/spec/v1
+oid sha256:09c4aa885c57dc5e3b49914d29f35f88d1e32e5db1ce05d9388c6768a768ad25
 size 109086416