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---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fresh-2-layer-medmcqa50000-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-medmcqa50000-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: 6.3481
- Accuracy: 0.7677
## 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 | 0.06 | 100 | 14.8949 | 0.4141 |
| No log | 0.13 | 200 | 11.8675 | 0.4697 |
| No log | 0.19 | 300 | 10.6894 | 0.5556 |
| No log | 0.26 | 400 | 9.8194 | 0.5404 |
| 3.5537 | 0.32 | 500 | 9.0542 | 0.5556 |
| 3.5537 | 0.38 | 600 | 9.0155 | 0.6061 |
| 3.5537 | 0.45 | 700 | 8.1758 | 0.6768 |
| 3.5537 | 0.51 | 800 | 7.6983 | 0.6970 |
| 3.5537 | 0.58 | 900 | 7.6211 | 0.6818 |
| 1.0971 | 0.64 | 1000 | 7.1361 | 0.6919 |
| 1.0971 | 0.7 | 1100 | 7.1059 | 0.6717 |
| 1.0971 | 0.77 | 1200 | 6.9443 | 0.6919 |
| 1.0971 | 0.83 | 1300 | 6.7089 | 0.7273 |
| 1.0971 | 0.9 | 1400 | 6.5064 | 0.7172 |
| 0.699 | 0.96 | 1500 | 5.9161 | 0.7273 |
| 0.699 | 1.02 | 1600 | 6.6374 | 0.7525 |
| 0.699 | 1.09 | 1700 | 6.3481 | 0.7677 |
| 0.699 | 1.15 | 1800 | 5.9385 | 0.7323 |
| 0.699 | 1.22 | 1900 | 6.2063 | 0.7374 |
| 0.4733 | 1.28 | 2000 | 5.9173 | 0.7273 |
| 0.4733 | 1.34 | 2100 | 5.8466 | 0.7626 |
| 0.4733 | 1.41 | 2200 | 5.6702 | 0.7374 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0
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