877a39be-52ef-4a81-bd46-d5f4b4328ba0
This model is a fine-tuned version of NousResearch/CodeLlama-7b-hf on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5760
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: 0.000203
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 500
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.0003 | 1 | 1.7362 |
| 3.4063 | 0.0154 | 50 | 1.6450 |
| 3.4891 | 0.0308 | 100 | 1.6377 |
| 3.4317 | 0.0462 | 150 | 1.6205 |
| 3.4055 | 0.0616 | 200 | 1.6160 |
| 3.365 | 0.0770 | 250 | 1.6015 |
| 3.3706 | 0.0924 | 300 | 1.5944 |
| 3.2789 | 0.1079 | 350 | 1.5833 |
| 3.2535 | 0.1233 | 400 | 1.5784 |
| 3.2544 | 0.1387 | 450 | 1.5762 |
| 3.514 | 0.1541 | 500 | 1.5760 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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Base model
NousResearch/CodeLlama-7b-hf