lora_0-1_3B
This model is a fine-tuned version of meta-llama/Llama-3.2-3B on the gulaschnascher4000/stream-dataset-0-2 and the identity-chatgulaschpt datasets. It achieves the following results on the evaluation set:
- Loss: 1.6369
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: 8
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 4
- optimizer: Use OptimizerNames.ADAFACTOR and the args are: scale_parameter=True, relative_step=True, warmup_init=True, lr=None
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.6471 | 0.4505 | 500 | 1.7360 |
| 1.6062 | 0.9009 | 1000 | 1.6384 |
Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
meta-llama/Llama-3.2-3B