---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fresh-2-layer-piqa5000-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-piqa5000-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: 13.3644
- Accuracy: 0.4444

## 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        | 0.64  | 100  | 16.9077         | 0.2677   |
| No log        | 1.27  | 200  | 16.7142         | 0.3333   |
| No log        | 1.91  | 300  | 13.9095         | 0.3131   |
| No log        | 2.55  | 400  | 16.4004         | 0.3838   |
| 2.6921        | 3.18  | 500  | 13.3775         | 0.3939   |
| 2.6921        | 3.82  | 600  | 15.2723         | 0.4091   |
| 2.6921        | 4.46  | 700  | 13.8835         | 0.3939   |
| 2.6921        | 5.1   | 800  | 13.7036         | 0.4242   |
| 2.6921        | 5.73  | 900  | 14.1660         | 0.4293   |
| 0.7686        | 6.37  | 1000 | 15.2431         | 0.4394   |
| 0.7686        | 7.01  | 1100 | 14.4889         | 0.3838   |
| 0.7686        | 7.64  | 1200 | 14.0171         | 0.3889   |
| 0.7686        | 8.28  | 1300 | 13.3644         | 0.4444   |
| 0.7686        | 8.92  | 1400 | 13.8387         | 0.4192   |
| 0.3654        | 9.55  | 1500 | 14.4017         | 0.3838   |
| 0.3654        | 10.19 | 1600 | 13.9023         | 0.4293   |
| 0.3654        | 10.83 | 1700 | 15.1041         | 0.4091   |
| 0.3654        | 11.46 | 1800 | 14.6756         | 0.4141   |


### Framework versions

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