---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fresh-2-layer-medmcqa20000-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-medmcqa20000-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: 6.0579
- 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        | 0.16  | 100  | 15.7756         | 0.3838   |
| No log        | 0.32  | 200  | 11.4980         | 0.5152   |
| No log        | 0.48  | 300  | 9.4964          | 0.5909   |
| No log        | 0.64  | 400  | 8.9627          | 0.6212   |
| 3.5065        | 0.8   | 500  | 8.5232          | 0.6061   |
| 3.5065        | 0.96  | 600  | 7.7951          | 0.6717   |
| 3.5065        | 1.12  | 700  | 8.2685          | 0.6616   |
| 3.5065        | 1.28  | 800  | 7.1380          | 0.6869   |
| 3.5065        | 1.44  | 900  | 7.3768          | 0.6818   |
| 0.9883        | 1.6   | 1000 | 6.9322          | 0.6970   |
| 0.9883        | 1.76  | 1100 | 6.7062          | 0.6818   |
| 0.9883        | 1.92  | 1200 | 6.6068          | 0.6919   |
| 0.9883        | 2.08  | 1300 | 6.3543          | 0.6818   |
| 0.9883        | 2.24  | 1400 | 6.0225          | 0.7020   |
| 0.5892        | 2.4   | 1500 | 6.6609          | 0.6667   |
| 0.5892        | 2.56  | 1600 | 6.3811          | 0.6919   |
| 0.5892        | 2.72  | 1700 | 6.2649          | 0.6970   |
| 0.5892        | 2.88  | 1800 | 6.8477          | 0.6919   |
| 0.5892        | 3.04  | 1900 | 5.6575          | 0.7071   |
| 0.4134        | 3.2   | 2000 | 5.8076          | 0.7071   |
| 0.4134        | 3.36  | 2100 | 6.0579          | 0.7222   |
| 0.4134        | 3.52  | 2200 | 5.7613          | 0.6970   |
| 0.4134        | 3.68  | 2300 | 5.6748          | 0.7222   |
| 0.4134        | 3.84  | 2400 | 5.8306          | 0.7121   |
| 0.3115        | 4.0   | 2500 | 5.7578          | 0.7071   |
| 0.3115        | 4.16  | 2600 | 5.5201          | 0.7172   |


### Framework versions

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