---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fresh-2-layer-medmcqa-distill-of-fresh-2-layer-medmcqa-distill-of-fresh-2-layer-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-medmcqa-distill-of-fresh-2-layer-medmcqa-distill-of-fresh-2-layer-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: 0.9186
- Accuracy: 0.5152

## 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: 16
- eval_batch_size: 16
- seed: 321
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 63   | 4.2492          | 0.2727   |
| No log        | 2.0   | 126  | 3.2851          | 0.3889   |
| No log        | 3.0   | 189  | 2.1889          | 0.4444   |
| No log        | 4.0   | 252  | 4.3537          | 0.4646   |
| No log        | 5.0   | 315  | 1.4476          | 0.4697   |
| No log        | 6.0   | 378  | 1.1196          | 0.4646   |
| No log        | 7.0   | 441  | 1.5751          | 0.4646   |
| 2.425         | 8.0   | 504  | 0.9802          | 0.4343   |
| 2.425         | 9.0   | 567  | 2.4061          | 0.4495   |
| 2.425         | 10.0  | 630  | 0.9186          | 0.5152   |
| 2.425         | 11.0  | 693  | 0.9569          | 0.4848   |
| 2.425         | 12.0  | 756  | 0.9649          | 0.4798   |
| 2.425         | 13.0  | 819  | 1.3807          | 0.4899   |
| 2.425         | 14.0  | 882  | 0.6900          | 0.4899   |
| 2.425         | 15.0  | 945  | 0.8787          | 0.4747   |
| 0.3146        | 16.0  | 1008 | 0.7985          | 0.4949   |
| 0.3146        | 17.0  | 1071 | 0.9305          | 0.4899   |
| 0.3146        | 18.0  | 1134 | 0.9062          | 0.4848   |
| 0.3146        | 19.0  | 1197 | 0.8571          | 0.5051   |
| 0.3146        | 20.0  | 1260 | 0.8674          | 0.5      |


### Framework versions

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