Llama3-Medical-Finetune_QA_MCQ
This model is a fine-tuned version of unsloth/llama-3-8b-bnb-4bit on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0295
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 2
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 5
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0399 | 0.5324 | 2000 | 1.0353 |
| 1.0358 | 1.0647 | 4000 | 1.0314 |
| 1.0278 | 1.5971 | 6000 | 1.0295 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for TachyHealthResearch/Llama3-Medical-Finetune_QA_MCQ
Base model
meta-llama/Meta-Llama-3-8B
Quantized
unsloth/llama-3-8b-bnb-4bit