metadata
tags:
- generated_from_trainer
model-index:
- name: src_prober_codellama-13b-last1unfreeze
results: []
src_prober_codellama-13b-last1unfreeze
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6267
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7443 | 0.12 | 500 | 0.7429 |
| 0.6851 | 0.24 | 1000 | 0.7170 |
| 0.6723 | 0.36 | 1500 | 0.6912 |
| 0.6605 | 0.48 | 2000 | 0.6730 |
| 0.6475 | 0.6 | 2500 | 0.6643 |
| 0.6419 | 0.72 | 3000 | 0.6584 |
| 0.6307 | 0.85 | 3500 | 0.6532 |
| 0.6167 | 0.97 | 4000 | 0.6495 |
| 0.6272 | 1.09 | 4500 | 0.6477 |
| 0.6002 | 1.21 | 5000 | 0.6445 |
| 0.6303 | 1.33 | 5500 | 0.6429 |
| 0.6405 | 1.45 | 6000 | 0.6421 |
| 0.6041 | 1.57 | 6500 | 0.6387 |
| 0.5912 | 1.69 | 7000 | 0.6370 |
| 0.6121 | 1.81 | 7500 | 0.6360 |
| 0.613 | 1.93 | 8000 | 0.6344 |
| 0.6126 | 2.05 | 8500 | 0.6338 |
| 0.5932 | 2.17 | 9000 | 0.6344 |
| 0.5927 | 2.3 | 9500 | 0.6332 |
| 0.5883 | 2.42 | 10000 | 0.6317 |
| 0.6023 | 2.54 | 10500 | 0.6308 |
| 0.5898 | 2.66 | 11000 | 0.6311 |
| 0.576 | 2.78 | 11500 | 0.6291 |
| 0.5699 | 2.9 | 12000 | 0.6291 |
| 0.6093 | 3.02 | 12500 | 0.6290 |
| 0.5754 | 3.14 | 13000 | 0.6292 |
| 0.6294 | 3.26 | 13500 | 0.6282 |
| 0.591 | 3.38 | 14000 | 0.6283 |
| 0.599 | 3.5 | 14500 | 0.6273 |
| 0.5933 | 3.62 | 15000 | 0.6281 |
| 0.565 | 3.75 | 15500 | 0.6268 |
| 0.5884 | 3.87 | 16000 | 0.6267 |
| 0.5809 | 3.99 | 16500 | 0.6266 |
| 0.5618 | 4.11 | 17000 | 0.6271 |
| 0.5749 | 4.23 | 17500 | 0.6274 |
| 0.577 | 4.35 | 18000 | 0.6268 |
| 0.5947 | 4.47 | 18500 | 0.6267 |
| 0.5902 | 4.59 | 19000 | 0.6268 |
| 0.5869 | 4.71 | 19500 | 0.6268 |
| 0.5829 | 4.83 | 20000 | 0.6268 |
| 0.5587 | 4.95 | 20500 | 0.6267 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.0
- Datasets 2.17.0
- Tokenizers 0.15.2