sparql-code-llama
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: 0.4088
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: 0.0003
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 400
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.695 | 0.0838 | 50 | 0.7324 |
| 0.4445 | 0.1676 | 100 | 0.5458 |
| 0.4184 | 0.2515 | 150 | 0.4852 |
| 0.4081 | 0.3353 | 200 | 0.4599 |
| 0.3996 | 0.4191 | 250 | 0.4389 |
| 0.3944 | 0.5029 | 300 | 0.4256 |
| 0.3925 | 0.5868 | 350 | 0.4150 |
| 0.3957 | 0.6706 | 400 | 0.4088 |
Framework versions
- PEFT 0.13.2
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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Base model
codellama/CodeLlama-7b-hf