zephyr-7b-sft-qlora
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the Dataset-t-t-t-t-t-t-t-t/UltraMed dataset. It achieves the following results on the evaluation set:
- Loss: 0.1659
Model description
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Intended uses & limitations
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Training and evaluation data
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Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.4852 | 1.0 | 134 | 0.1659 |
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 Dataset-t-t-t-t-t-t-t-t/zephyr-7b-sft-qlora
Base model
mistralai/Mistral-7B-v0.1