|
|
--- |
|
|
license: mit |
|
|
base_model: gpt2 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: codeparrot-ds |
|
|
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. --> |
|
|
|
|
|
# codeparrot-ds |
|
|
|
|
|
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: 5.1291 |
|
|
|
|
|
## 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: 42 |
|
|
- gradient_accumulation_steps: 8 |
|
|
- total_train_batch_size: 256 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: cosine |
|
|
- lr_scheduler_warmup_steps: 10 |
|
|
- num_epochs: 5 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|
|:-------------:|:------:|:----:|:---------------:| |
|
|
| 9.5166 | 0.2332 | 10 | 7.9560 | |
|
|
| 7.161 | 0.4665 | 20 | 6.8948 | |
|
|
| 6.7973 | 0.6997 | 30 | 6.7108 | |
|
|
| 6.4652 | 0.9329 | 40 | 6.3878 | |
|
|
| 6.1192 | 1.1662 | 50 | 6.1154 | |
|
|
| 5.842 | 1.3994 | 60 | 5.8976 | |
|
|
| 5.6262 | 1.6327 | 70 | 5.7493 | |
|
|
| 5.4633 | 1.8659 | 80 | 5.6221 | |
|
|
| 5.3212 | 2.0991 | 90 | 5.5376 | |
|
|
| 5.1513 | 2.3324 | 100 | 5.4584 | |
|
|
| 5.118 | 2.5656 | 110 | 5.3924 | |
|
|
| 4.9714 | 2.7988 | 120 | 5.3301 | |
|
|
| 4.9133 | 3.0321 | 130 | 5.2827 | |
|
|
| 4.7702 | 3.2653 | 140 | 5.2460 | |
|
|
| 4.7302 | 3.4985 | 150 | 5.2081 | |
|
|
| 4.6988 | 3.7318 | 160 | 5.1740 | |
|
|
| 4.6927 | 3.9650 | 170 | 5.1537 | |
|
|
| 4.6044 | 4.1983 | 180 | 5.1442 | |
|
|
| 4.5763 | 4.4315 | 190 | 5.1361 | |
|
|
| 4.5913 | 4.6647 | 200 | 5.1298 | |
|
|
| 4.5759 | 4.8980 | 210 | 5.1291 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.41.2 |
|
|
- Pytorch 2.3.0+cu121 |
|
|
- Datasets 2.20.0 |
|
|
- Tokenizers 0.19.1 |
|
|
|
