c08f8dc4-e5ba-4221-aafa-dbd63b6f53a9
This model is a fine-tuned version of NousResearch/CodeLlama-13b-hf on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6809
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: 0.000206
- 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: 280
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 0.0018 | 1 | 3.3431 |
1.6233 | 0.0894 | 50 | 1.2710 |
2.8082 | 0.1787 | 100 | 1.2992 |
1.2803 | 0.2681 | 150 | 0.9687 |
1.4953 | 0.3575 | 200 | 0.7798 |
1.3409 | 0.4468 | 250 | 0.6809 |
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-13b-hf