metadata
license: llama2
base_model: codellama/CodeLlama-13b-Instruct-hf
tags:
- generated_from_trainer
metrics:
- accuracy
- bleu
- sacrebleu
- rouge
model-index:
- name: >-
CodeLlama-13b-Instruct-hf_En__size_52_epochs_10_2024-06-21_06-37-42_3556410
results: []
CodeLlama-13b-Instruct-hf_En__size_52_epochs_10_2024-06-21_06-37-42_3556410
This model is a fine-tuned version of codellama/CodeLlama-13b-Instruct-hf on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6986
- Accuracy: 0.052
- Chrf: 0.682
- Bleu: 0.599
- Sacrebleu: 0.6
- Rouge1: 0.651
- Rouge2: 0.434
- Rougel: 0.601
- Rougelsum: 0.644
- Meteor: 0.54
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: 1
- eval_batch_size: 1
- seed: 3407
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 4
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 52
- training_steps: 520
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Chrf | Bleu | Sacrebleu | Rouge1 | Rouge2 | Rougel | Rougelsum | Meteor |
---|---|---|---|---|---|---|---|---|---|---|---|---|
0.5377 | 4.0 | 52 | 1.6208 | 0.06 | 0.637 | 0.525 | 0.5 | 0.619 | 0.387 | 0.564 | 0.608 | 0.488 |
0.932 | 8.0 | 104 | 2.1202 | 0.05 | 0.554 | 0.452 | 0.5 | 0.569 | 0.313 | 0.515 | 0.566 | 0.485 |
0.3679 | 12.0 | 156 | 1.9634 | 0.049 | 0.606 | 0.488 | 0.5 | 0.594 | 0.371 | 0.549 | 0.59 | 0.491 |
0.3454 | 16.0 | 208 | 1.9613 | 0.053 | 0.601 | 0.487 | 0.5 | 0.571 | 0.325 | 0.524 | 0.566 | 0.504 |
0.3294 | 20.0 | 260 | 1.8641 | 0.05 | 0.638 | 0.536 | 0.5 | 0.611 | 0.388 | 0.568 | 0.604 | 0.516 |
0.5272 | 24.0 | 312 | 1.8354 | 0.052 | 0.644 | 0.535 | 0.5 | 0.609 | 0.368 | 0.559 | 0.603 | 0.531 |
0.1871 | 28.0 | 364 | 1.7705 | 0.054 | 0.659 | 0.568 | 0.6 | 0.627 | 0.41 | 0.586 | 0.624 | 0.54 |
0.4867 | 32.0 | 416 | 1.7689 | 0.052 | 0.665 | 0.571 | 0.6 | 0.63 | 0.406 | 0.579 | 0.624 | 0.562 |
0.1634 | 36.0 | 468 | 1.6964 | 0.052 | 0.682 | 0.601 | 0.6 | 0.658 | 0.444 | 0.605 | 0.65 | 0.538 |
0.3475 | 40.0 | 520 | 1.6986 | 0.052 | 0.682 | 0.599 | 0.6 | 0.651 | 0.434 | 0.601 | 0.644 | 0.54 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.2.1+cu121
- Datasets 2.20.0
- Tokenizers 0.15.2