medicalQA_1b_4
This model is a fine-tuned version of meta-llama/Llama-3.2-1B-Instruct on the MedQA2 and the Med_int_data datasets. It achieves the following results on the evaluation set:
- Loss: 1.9075
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: 5e-07
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.6521 | 0.6254 | 500 | 1.9213 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 2.21.0
- Tokenizers 0.20.3
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Model tree for Johhny1201/llama3.2_1b_med_QA_3
Base model
meta-llama/Llama-3.2-1B-Instruct