---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fresh-2-layer-qasc5000-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-qasc5000-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: 14.9541
- Accuracy: 0.4949

## 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  | 14.0782         | 0.3131   |
| No log        | 1.27  | 200  | 15.6534         | 0.4596   |
| No log        | 1.91  | 300  | 16.2410         | 0.4293   |
| No log        | 2.55  | 400  | 14.4394         | 0.4495   |
| 1.861         | 3.18  | 500  | 15.1088         | 0.4646   |
| 1.861         | 3.82  | 600  | 14.4621         | 0.4848   |
| 1.861         | 4.46  | 700  | 15.0037         | 0.4596   |
| 1.861         | 5.1   | 800  | 15.6656         | 0.4293   |
| 1.861         | 5.73  | 900  | 15.1955         | 0.4343   |
| 0.2711        | 6.37  | 1000 | 14.9541         | 0.4949   |
| 0.2711        | 7.01  | 1100 | 14.5891         | 0.4646   |
| 0.2711        | 7.64  | 1200 | 15.4136         | 0.4747   |
| 0.2711        | 8.28  | 1300 | 15.4486         | 0.4697   |
| 0.2711        | 8.92  | 1400 | 14.5015         | 0.4848   |
| 0.1568        | 9.55  | 1500 | 14.2260         | 0.4545   |


### Framework versions

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