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---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fresh-2-layer-medmcqa20000-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-medmcqa20000-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: 5.6554
- Accuracy: 0.7323
## 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 | 0.16 | 100 | 15.6094 | 0.3384 |
| No log | 0.32 | 200 | 11.2486 | 0.4747 |
| No log | 0.48 | 300 | 9.7003 | 0.5556 |
| No log | 0.64 | 400 | 9.0128 | 0.6212 |
| 3.508 | 0.8 | 500 | 9.0146 | 0.6111 |
| 3.508 | 0.96 | 600 | 7.8672 | 0.6465 |
| 3.508 | 1.12 | 700 | 7.4123 | 0.6768 |
| 3.508 | 1.28 | 800 | 7.4161 | 0.6515 |
| 3.508 | 1.44 | 900 | 7.3679 | 0.6667 |
| 0.9934 | 1.6 | 1000 | 6.8781 | 0.6768 |
| 0.9934 | 1.76 | 1100 | 6.7447 | 0.6717 |
| 0.9934 | 1.92 | 1200 | 7.6242 | 0.6818 |
| 0.9934 | 2.08 | 1300 | 6.6278 | 0.6869 |
| 0.9934 | 2.24 | 1400 | 6.4569 | 0.6970 |
| 0.6102 | 2.4 | 1500 | 6.7556 | 0.7121 |
| 0.6102 | 2.56 | 1600 | 6.3065 | 0.7020 |
| 0.6102 | 2.72 | 1700 | 6.2906 | 0.7071 |
| 0.6102 | 2.88 | 1800 | 6.2230 | 0.7121 |
| 0.6102 | 3.04 | 1900 | 6.9069 | 0.7172 |
| 0.4278 | 3.2 | 2000 | 6.0706 | 0.7172 |
| 0.4278 | 3.36 | 2100 | 6.0340 | 0.7172 |
| 0.4278 | 3.52 | 2200 | 5.6554 | 0.7323 |
| 0.4278 | 3.68 | 2300 | 5.8829 | 0.7020 |
| 0.4278 | 3.84 | 2400 | 5.6822 | 0.7222 |
| 0.3174 | 4.0 | 2500 | 5.7620 | 0.7222 |
| 0.3174 | 4.16 | 2600 | 5.7952 | 0.7172 |
| 0.3174 | 4.32 | 2700 | 5.6193 | 0.7222 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0
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