---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fresh-2-layer-qasc2000-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-qasc2000-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: 14.9062
- Accuracy: 0.4192

## 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        | 1.59  | 100  | 14.0964         | 0.2980   |
| No log        | 3.17  | 200  | 15.9598         | 0.3788   |
| No log        | 4.76  | 300  | 14.9387         | 0.4091   |
| No log        | 6.35  | 400  | 14.1750         | 0.4091   |
| 1.6819        | 7.94  | 500  | 16.7634         | 0.4091   |
| 1.6819        | 9.52  | 600  | 14.9062         | 0.4192   |
| 1.6819        | 11.11 | 700  | 13.9546         | 0.4091   |
| 1.6819        | 12.7  | 800  | 14.2041         | 0.4091   |
| 1.6819        | 14.29 | 900  | 15.2506         | 0.4040   |
| 0.2306        | 15.87 | 1000 | 14.9041         | 0.4091   |
| 0.2306        | 17.46 | 1100 | 14.9118         | 0.4141   |


### Framework versions

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