---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fresh-2-layer-medmcqa5000-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-medmcqa5000-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: 8.7386
- Accuracy: 0.6465

## 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  | 13.7722         | 0.3384   |
| No log        | 1.27  | 200  | 11.9604         | 0.4293   |
| No log        | 1.91  | 300  | 10.3469         | 0.5253   |
| No log        | 2.55  | 400  | 10.4306         | 0.5657   |
| 3.3633        | 3.18  | 500  | 9.3915          | 0.6414   |
| 3.3633        | 3.82  | 600  | 8.7386          | 0.6465   |
| 3.3633        | 4.46  | 700  | 8.8047          | 0.6212   |
| 3.3633        | 5.1   | 800  | 9.3199          | 0.5960   |
| 3.3633        | 5.73  | 900  | 8.1435          | 0.6364   |
| 0.7294        | 6.37  | 1000 | 8.3517          | 0.6313   |
| 0.7294        | 7.01  | 1100 | 8.8800          | 0.6111   |


### Framework versions

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