---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fresh-2-layer-medmcqa10000-distill-of-fresh-2-layer-gpqa_EVAL_gpqa
  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. -->

# fresh-2-layer-medmcqa10000-distill-of-fresh-2-layer-gpqa_EVAL_gpqa

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 7.2371
- Accuracy: 0.7222

## 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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 321
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.32  | 100  | 13.8640         | 0.4495   |
| No log        | 0.64  | 200  | 11.8895         | 0.5152   |
| No log        | 0.96  | 300  | 10.3828         | 0.5303   |
| No log        | 1.28  | 400  | 9.0300          | 0.5657   |
| 3.3496        | 1.6   | 500  | 8.6264          | 0.5808   |
| 3.3496        | 1.92  | 600  | 8.8207          | 0.6061   |
| 3.3496        | 2.24  | 700  | 8.8302          | 0.5960   |
| 3.3496        | 2.56  | 800  | 8.8428          | 0.6566   |
| 3.3496        | 2.88  | 900  | 7.9552          | 0.6364   |
| 0.8968        | 3.19  | 1000 | 8.4617          | 0.6263   |
| 0.8968        | 3.51  | 1100 | 8.8555          | 0.6616   |
| 0.8968        | 3.83  | 1200 | 7.5445          | 0.6566   |
| 0.8968        | 4.15  | 1300 | 7.6791          | 0.6717   |
| 0.8968        | 4.47  | 1400 | 7.8363          | 0.6616   |
| 0.4853        | 4.79  | 1500 | 7.6269          | 0.6515   |
| 0.4853        | 5.11  | 1600 | 7.5024          | 0.6919   |
| 0.4853        | 5.43  | 1700 | 7.4191          | 0.6717   |
| 0.4853        | 5.75  | 1800 | 7.6877          | 0.6768   |
| 0.4853        | 6.07  | 1900 | 7.4651          | 0.6818   |
| 0.3197        | 6.39  | 2000 | 7.4452          | 0.6970   |
| 0.3197        | 6.71  | 2100 | 7.2401          | 0.7121   |
| 0.3197        | 7.03  | 2200 | 7.4038          | 0.7121   |
| 0.3197        | 7.35  | 2300 | 7.1982          | 0.7071   |
| 0.3197        | 7.67  | 2400 | 7.2287          | 0.7071   |
| 0.2394        | 7.99  | 2500 | 7.2371          | 0.7222   |
| 0.2394        | 8.31  | 2600 | 7.2513          | 0.7071   |
| 0.2394        | 8.63  | 2700 | 7.3788          | 0.6919   |
| 0.2394        | 8.95  | 2800 | 7.1303          | 0.7071   |
| 0.2394        | 9.27  | 2900 | 7.1608          | 0.7121   |
| 0.1744        | 9.58  | 3000 | 7.1039          | 0.7222   |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0