---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fresh-2-layer-swag20000-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-swag20000-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: 15.3688
- Accuracy: 0.4747

## 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  | 14.6793         | 0.2677   |
| No log        | 0.32  | 200  | 21.2273         | 0.3687   |
| No log        | 0.48  | 300  | 19.4173         | 0.3485   |
| No log        | 0.64  | 400  | 23.6541         | 0.4343   |
| 2.2803        | 0.8   | 500  | 18.0346         | 0.4091   |
| 2.2803        | 0.96  | 600  | 20.1434         | 0.4293   |
| 2.2803        | 1.12  | 700  | 16.6838         | 0.4192   |
| 2.2803        | 1.28  | 800  | 15.3688         | 0.4747   |
| 2.2803        | 1.44  | 900  | 16.6134         | 0.4444   |
| 0.5776        | 1.6   | 1000 | 15.2527         | 0.4192   |
| 0.5776        | 1.76  | 1100 | 13.8964         | 0.4444   |
| 0.5776        | 1.92  | 1200 | 15.0290         | 0.4444   |
| 0.5776        | 2.08  | 1300 | 14.4659         | 0.4495   |


### Framework versions

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