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---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: gpt2_cfg_add_8
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. -->
# gpt2_cfg_add_8
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: 0.0000
- Accuracy: 1.0
## 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: 0.001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.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: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log | 0 | 0 | 2.7379 | 0.0 |
| 1.9725 | 0.0320 | 100 | 1.9286 | 0.0 |
| 1.0948 | 0.0641 | 200 | 0.9757 | 0.02 |
| 0.6137 | 0.0961 | 300 | 0.6562 | 0.09 |
| 0.3684 | 0.1281 | 400 | 0.3644 | 0.35 |
| 0.2853 | 0.1602 | 500 | 0.2482 | 0.61 |
| 0.0578 | 0.1922 | 600 | 0.0728 | 0.84 |
| 0.0081 | 0.2242 | 700 | 0.0669 | 0.88 |
| 0.0033 | 0.2562 | 800 | 0.0264 | 0.93 |
| 2.4737 | 0.2883 | 900 | 1.5848 | 0.005 |
| 0.0482 | 0.3203 | 1000 | 0.0470 | 0.89 |
| 0.0009 | 0.3523 | 1100 | 0.0078 | 0.985 |
| 0.0125 | 0.3844 | 1200 | 0.0068 | 0.98 |
| 0.005 | 0.4164 | 1300 | 0.0116 | 0.975 |
| 0.0256 | 0.4484 | 1400 | 0.0035 | 0.995 |
| 0.0003 | 0.4805 | 1500 | 0.0005 | 1.0 |
| 0.0001 | 0.5125 | 1600 | 0.0001 | 1.0 |
| 0.0 | 0.5445 | 1700 | 0.0000 | 1.0 |
| 0.0 | 0.5766 | 1800 | 0.0000 | 1.0 |
| 0.0001 | 0.6086 | 1900 | 0.0002 | 1.0 |
| 0.0 | 0.6406 | 2000 | 0.0000 | 1.0 |
| 0.0 | 0.6726 | 2100 | 0.0000 | 1.0 |
| 0.0 | 0.7047 | 2200 | 0.0000 | 1.0 |
| 0.0 | 0.7367 | 2300 | 0.0000 | 1.0 |
| 0.0 | 0.7687 | 2400 | 0.0000 | 1.0 |
| 0.0 | 0.8008 | 2500 | 0.0000 | 1.0 |
| 0.0 | 0.8328 | 2600 | 0.0000 | 1.0 |
| 0.0 | 0.8648 | 2700 | 0.0000 | 1.0 |
| 0.0 | 0.8969 | 2800 | 0.0000 | 1.0 |
| 0.0 | 0.9289 | 2900 | 0.0000 | 1.0 |
| 0.0 | 0.9609 | 3000 | 0.0000 | 1.0 |
| 0.0 | 0.9930 | 3100 | 0.0000 | 1.0 |
### Framework versions
- Transformers 4.46.0
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.1
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