fine_tuned_model_llama-3.2
This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7120
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: 16
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.9301 | 0.9302 | 200 | 1.8595 |
| 1.7509 | 1.8605 | 400 | 1.7878 |
| 1.648 | 2.7907 | 600 | 1.7535 |
| 1.5729 | 3.7209 | 800 | 1.7286 |
| 1.5075 | 4.6512 | 1000 | 1.7161 |
| 1.4594 | 5.5814 | 1200 | 1.7090 |
| 1.4029 | 6.5116 | 1400 | 1.7080 |
| 1.3623 | 7.4419 | 1600 | 1.7088 |
| 1.3274 | 8.3721 | 1800 | 1.7128 |
| 1.301 | 9.3023 | 2000 | 1.7120 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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Model tree for Akshit-77/fine_tuned_model_llama-3.2
Base model
meta-llama/Llama-3.2-3B-Instruct