codellama-instruct-mojo
This model is a fine-tuned version of meta-llama/CodeLlama-7b-Instruct-hf on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0479
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: 0.0002
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.7563 | 1.0 | 50 | 1.2784 |
1.1544 | 2.0 | 100 | 1.0706 |
0.8205 | 3.0 | 150 | 1.0189 |
0.6381 | 4.0 | 200 | 1.0038 |
0.4976 | 5.0 | 250 | 1.0479 |
Framework versions
- PEFT 0.12.1.dev0
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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Model tree for annaluiza/codellama-instruct-mojo
Base model
meta-llama/CodeLlama-7b-Instruct-hf