2a0ebbaa-779c-4ec1-a3ac-8de72b3522b7
This model is a fine-tuned version of sethuiyer/Medichat-Llama3-8B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6928
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: 0.00021
- train_batch_size: 4
- eval_batch_size: 4
- seed: 100
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 500
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.0010 | 1 | 3.6882 |
| 1.8659 | 0.0500 | 50 | 2.0637 |
| 1.9695 | 0.0999 | 100 | 2.0315 |
| 1.7599 | 0.1499 | 150 | 2.0024 |
| 1.5861 | 0.1998 | 200 | 2.0269 |
| 1.6931 | 0.2498 | 250 | 1.9456 |
| 1.84 | 0.2997 | 300 | 1.8212 |
| 1.674 | 0.3497 | 350 | 1.7681 |
| 1.8363 | 0.3996 | 400 | 1.7177 |
| 1.517 | 0.4496 | 450 | 1.6950 |
| 1.6894 | 0.4995 | 500 | 1.6928 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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Base model
sethuiyer/Medichat-Llama3-8B