student_sft_init
This model is a fine-tuned version of meta-llama/Llama-3.2-1B on the HuggingFaceH4/deita-10k-v0-sft dataset. It achieves the following results on the evaluation set:
- Loss: 1.1643
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 256
- total_eval_batch_size: 128
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0918 | 1.0 | 143 | 1.1571 |
| 0.9824 | 2.0 | 286 | 1.1501 |
| 0.9069 | 3.0 | 429 | 1.1643 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 4.8.5
- Tokenizers 0.21.4