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---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fresh-2-layer-medmcqa-distill-of-fresh-2-layer-gpqa-loop-5
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-medmcqa-distill-of-fresh-2-layer-gpqa-loop-5
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: 0.4393
- 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: 16
- eval_batch_size: 16
- seed: 321
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 63 | 2.3938 | 0.2475 |
| No log | 2.0 | 126 | 1.5164 | 0.3636 |
| No log | 3.0 | 189 | 1.1653 | 0.4646 |
| No log | 4.0 | 252 | 0.7958 | 0.4394 |
| No log | 5.0 | 315 | 0.5525 | 0.4596 |
| No log | 6.0 | 378 | 1.1572 | 0.4747 |
| No log | 7.0 | 441 | 0.3450 | 0.4798 |
| 1.7802 | 8.0 | 504 | 0.4393 | 0.5202 |
| 1.7802 | 9.0 | 567 | 0.5459 | 0.4343 |
| 1.7802 | 10.0 | 630 | 0.4935 | 0.5101 |
| 1.7802 | 11.0 | 693 | 0.3405 | 0.4697 |
| 1.7802 | 12.0 | 756 | 0.3275 | 0.4697 |
| 1.7802 | 13.0 | 819 | 0.2442 | 0.4646 |
| 1.7802 | 14.0 | 882 | 0.2561 | 0.4495 |
| 1.7802 | 15.0 | 945 | 0.2196 | 0.4495 |
| 0.215 | 16.0 | 1008 | 0.1943 | 0.4495 |
| 0.215 | 17.0 | 1071 | 0.1845 | 0.4545 |
| 0.215 | 18.0 | 1134 | 0.1702 | 0.4444 |
| 0.215 | 19.0 | 1197 | 0.1788 | 0.4545 |
| 0.215 | 20.0 | 1260 | 0.1747 | 0.4545 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0
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