metadata
tags:
- generated_from_trainer
model-index:
- name: src_prober_codellama-7b-last1unfreeze
results: []
src_prober_codellama-7b-last1unfreeze
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6729
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: 8
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 128
- 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 |
|---|---|---|---|
| 0.7634 | 0.24 | 500 | 0.7745 |
| 0.7376 | 0.48 | 1000 | 0.7399 |
| 0.7006 | 0.72 | 1500 | 0.7138 |
| 0.6721 | 0.97 | 2000 | 0.7015 |
| 0.6753 | 1.21 | 2500 | 0.6941 |
| 0.6716 | 1.45 | 3000 | 0.6894 |
| 0.6595 | 1.69 | 3500 | 0.6865 |
| 0.6743 | 1.93 | 4000 | 0.6848 |
| 0.6647 | 2.17 | 4500 | 0.6819 |
| 0.6721 | 2.42 | 5000 | 0.6797 |
| 0.6642 | 2.66 | 5500 | 0.6780 |
| 0.6653 | 2.9 | 6000 | 0.6764 |
| 0.643 | 3.14 | 6500 | 0.6756 |
| 0.6532 | 3.38 | 7000 | 0.6749 |
| 0.6299 | 3.62 | 7500 | 0.6745 |
| 0.6442 | 3.87 | 8000 | 0.6737 |
| 0.6347 | 4.11 | 8500 | 0.6733 |
| 0.6364 | 4.35 | 9000 | 0.6730 |
| 0.6456 | 4.59 | 9500 | 0.6728 |
| 0.6338 | 4.83 | 10000 | 0.6729 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.0
- Datasets 2.17.0
- Tokenizers 0.15.2