finetuned_llama
This model is a fine-tuned version of unsloth/llama-3-8b-bnb-4bit on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.6510
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.7203 | 0.9923 | 97 | 2.6799 |
| 2.6812 | 1.9923 | 194 | 2.6539 |
| 2.6559 | 2.9923 | 291 | 2.6510 |
Framework versions
- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for josty11/finetuned_llama
Base model
meta-llama/Meta-Llama-3-8B
Quantized
unsloth/llama-3-8b-bnb-4bit