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---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fresh-2-layer-medmcqa-distill-of-fresh-2-layer-medmcqa-distill-of-fresh-2-layer-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-medmcqa-distill-of-fresh-2-layer-medmcqa-distill-of-fresh-2-layer-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: 0.9186
- Accuracy: 0.5152
## 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 | 4.2492 | 0.2727 |
| No log | 2.0 | 126 | 3.2851 | 0.3889 |
| No log | 3.0 | 189 | 2.1889 | 0.4444 |
| No log | 4.0 | 252 | 4.3537 | 0.4646 |
| No log | 5.0 | 315 | 1.4476 | 0.4697 |
| No log | 6.0 | 378 | 1.1196 | 0.4646 |
| No log | 7.0 | 441 | 1.5751 | 0.4646 |
| 2.425 | 8.0 | 504 | 0.9802 | 0.4343 |
| 2.425 | 9.0 | 567 | 2.4061 | 0.4495 |
| 2.425 | 10.0 | 630 | 0.9186 | 0.5152 |
| 2.425 | 11.0 | 693 | 0.9569 | 0.4848 |
| 2.425 | 12.0 | 756 | 0.9649 | 0.4798 |
| 2.425 | 13.0 | 819 | 1.3807 | 0.4899 |
| 2.425 | 14.0 | 882 | 0.6900 | 0.4899 |
| 2.425 | 15.0 | 945 | 0.8787 | 0.4747 |
| 0.3146 | 16.0 | 1008 | 0.7985 | 0.4949 |
| 0.3146 | 17.0 | 1071 | 0.9305 | 0.4899 |
| 0.3146 | 18.0 | 1134 | 0.9062 | 0.4848 |
| 0.3146 | 19.0 | 1197 | 0.8571 | 0.5051 |
| 0.3146 | 20.0 | 1260 | 0.8674 | 0.5 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0
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