sft2
This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on the train dataset. It achieves the following results on the evaluation set:
- Loss: 0.2533
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: 1e-05
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.1653 | 1.5432 | 500 | 0.2352 |
Framework versions
- Transformers 4.45.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.20.0
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