llama3.1-mini-QLoRA
This model is a fine-tuned version of meta-llama/Llama-3.2-1B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6375
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: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.9432 | 1.5810 | 100 | 1.1024 |
1.049 | 3.1621 | 200 | 0.9510 |
0.9297 | 4.7431 | 300 | 0.8364 |
0.8233 | 6.3241 | 400 | 0.7393 |
0.7348 | 7.9051 | 500 | 0.6737 |
0.6697 | 9.4862 | 600 | 0.6375 |
Framework versions
- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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Model tree for Pragades/llama3.1-mini-QLoRA
Base model
meta-llama/Llama-3.2-1B