---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fresh-2-layer-piqa16113-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-piqa16113-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: 12.5601
- Accuracy: 0.5202

## 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        | 0.2   | 100  | 17.5725         | 0.2273   |
| No log        | 0.4   | 200  | 13.7753         | 0.3939   |
| No log        | 0.6   | 300  | 14.6182         | 0.3687   |
| No log        | 0.79  | 400  | 13.4422         | 0.3687   |
| 2.8312        | 0.99  | 500  | 12.2908         | 0.4242   |
| 2.8312        | 1.19  | 600  | 13.2865         | 0.3687   |
| 2.8312        | 1.39  | 700  | 12.8823         | 0.4596   |
| 2.8312        | 1.59  | 800  | 12.7374         | 0.4747   |
| 2.8312        | 1.79  | 900  | 14.0988         | 0.4848   |
| 1.0908        | 1.98  | 1000 | 12.8163         | 0.5      |
| 1.0908        | 2.18  | 1100 | 13.4111         | 0.5051   |
| 1.0908        | 2.38  | 1200 | 12.8755         | 0.4697   |
| 1.0908        | 2.58  | 1300 | 12.9406         | 0.5101   |
| 1.0908        | 2.78  | 1400 | 13.3437         | 0.4747   |
| 0.6569        | 2.98  | 1500 | 15.6074         | 0.4899   |
| 0.6569        | 3.17  | 1600 | 12.5601         | 0.5202   |
| 0.6569        | 3.37  | 1700 | 13.7042         | 0.5051   |
| 0.6569        | 3.57  | 1800 | 12.6509         | 0.4848   |
| 0.6569        | 3.77  | 1900 | 12.9618         | 0.5152   |
| 0.4619        | 3.97  | 2000 | 13.1769         | 0.4697   |
| 0.4619        | 4.17  | 2100 | 13.0498         | 0.4646   |


### Framework versions

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