metadata
license: llama2
library_name: peft
tags:
- generated_from_trainer
base_model: codellama/CodeLlama-7b-hf
model-index:
- name: fine-tuning-code_llama_lib_4
results: []
fine-tuning-code_llama_lib_4
This model is a fine-tuned version of codellama/CodeLlama-7b-hf on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1215
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: 3
- eval_batch_size: 3
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 15
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 60
- num_epochs: 11
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.7737 | 1.0 | 63 | 0.6034 |
0.4194 | 2.0 | 126 | 0.3423 |
0.2123 | 3.0 | 189 | 0.2168 |
0.1542 | 4.0 | 252 | 0.1721 |
0.1343 | 5.0 | 315 | 0.1508 |
0.1224 | 6.0 | 378 | 0.1395 |
0.1141 | 7.0 | 441 | 0.1321 |
0.1075 | 8.0 | 504 | 0.1273 |
0.1028 | 9.0 | 567 | 0.1243 |
0.0993 | 10.0 | 630 | 0.1220 |
0.0973 | 11.0 | 693 | 0.1215 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.2