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---
library_name: transformers
license: mit
base_model: gpt2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: js-fake-bach-epochs20
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. -->
# js-fake-bach-epochs20
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5973
- Accuracy: 0.0033
## 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: 0.0006058454513356471
- train_batch_size: 16
- eval_batch_size: 32
- seed: 1
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.2427 | 1.2550 | 315 | 0.8253 | 0.0007 |
| 0.8106 | 2.5100 | 630 | 0.7777 | 0.0021 |
| 0.7663 | 3.7649 | 945 | 0.7449 | 0.0017 |
| 0.7263 | 5.0199 | 1260 | 0.6997 | 0.0027 |
| 0.689 | 6.2749 | 1575 | 0.6683 | 0.0018 |
| 0.6524 | 7.5299 | 1890 | 0.6396 | 0.0008 |
| 0.6158 | 8.7849 | 2205 | 0.6139 | 0.0021 |
| 0.5807 | 10.0398 | 2520 | 0.5981 | 0.0010 |
| 0.5437 | 11.2948 | 2835 | 0.5848 | 0.0030 |
| 0.5109 | 12.5498 | 3150 | 0.5841 | 0.0026 |
| 0.4781 | 13.8048 | 3465 | 0.5799 | 0.0028 |
| 0.4453 | 15.0598 | 3780 | 0.5867 | 0.0034 |
| 0.4169 | 16.3147 | 4095 | 0.5915 | 0.0034 |
| 0.3972 | 17.5697 | 4410 | 0.5968 | 0.0034 |
| 0.3847 | 18.8247 | 4725 | 0.5973 | 0.0033 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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