|
|
--- |
|
|
license: mit |
|
|
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: 1.0626 |
|
|
|
|
|
## 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: 1000 |
|
|
- num_epochs: 1 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|
|:-------------:|:-----:|:-----:|:---------------:| |
|
|
| 2.5672 | 0.08 | 5000 | 1.7393 | |
|
|
| 1.6801 | 0.15 | 10000 | 1.5217 | |
|
|
| 1.5349 | 0.23 | 15000 | 1.4211 | |
|
|
| 1.4557 | 0.31 | 20000 | 1.3588 | |
|
|
| 1.3968 | 0.38 | 25000 | 1.3071 | |
|
|
| 1.3458 | 0.46 | 30000 | 1.2592 | |
|
|
| 1.2994 | 0.54 | 35000 | 1.2142 | |
|
|
| 1.2541 | 0.61 | 40000 | 1.1730 | |
|
|
| 1.2123 | 0.69 | 45000 | 1.1335 | |
|
|
| 1.175 | 0.77 | 50000 | 1.1012 | |
|
|
| 1.1454 | 0.84 | 55000 | 1.0777 | |
|
|
| 1.1247 | 0.92 | 60000 | 1.0652 | |
|
|
| 1.1168 | 1.0 | 65000 | 1.0626 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.24.0 |
|
|
- Pytorch 1.12.1+cu113 |
|
|
- Datasets 2.7.1 |
|
|
- Tokenizers 0.13.2 |
|
|
|
