llm3br256-v1.5
This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on the Klystroglobal dataset. It achieves the following results on the evaluation set:
- Loss: 0.0154
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: 0.0001
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 35
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0459 | 2.5 | 25 | 0.0362 |
| 0.0083 | 5.0 | 50 | 0.0184 |
| 0.0058 | 7.5 | 75 | 0.0171 |
| 0.0024 | 10.0 | 100 | 0.0154 |
| 0.0015 | 12.5 | 125 | 0.0164 |
| 0.0038 | 15.0 | 150 | 0.0210 |
| 0.0013 | 17.5 | 175 | 0.0282 |
| 0.0012 | 20.0 | 200 | 0.0279 |
| 0.0013 | 22.5 | 225 | 0.0306 |
Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.4.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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