---
library_name: peft
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: medllama3-v20-with-prefix_prompt
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# medllama3-v20-with-prefix_prompt

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co./meta-llama/Meta-Llama-3-8B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8028
- Balanced Accuracy: 0.5960
- Accuracy: 0.5457

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Balanced Accuracy | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------:|
| 1.7999        | 1.0   | 165  | 0.6813          | 0.6104            | 0.6187   |
| 1.7523        | 2.0   | 330  | 0.6623          | 0.5918            | 0.4087   |
| 2.1806        | 3.0   | 495  | 0.6799          | 0.6413            | 0.4269   |
| 1.3861        | 4.0   | 660  | 0.7232          | 0.6363            | 0.4452   |
| 1.6961        | 5.0   | 825  | 0.8122          | 0.6428            | 0.3721   |
| 1.4074        | 6.0   | 990  | 0.8685          | 0.6400            | 0.6735   |
| 1.3749        | 7.0   | 1155 | 0.6330          | 0.6409            | 0.6598   |
| 1.3455        | 8.0   | 1320 | 0.6396          | 0.6594            | 0.4886   |
| 1.3391        | 9.0   | 1485 | 0.6102          | 0.6464            | 0.5845   |
| 1.4026        | 10.0  | 1650 | 0.6464          | 0.6058            | 0.6142   |
| 1.2097        | 11.0  | 1815 | 0.7539          | 0.6151            | 0.6644   |
| 1.178         | 12.0  | 1980 | 0.6004          | 0.6539            | 0.6210   |
| 1.1876        | 13.0  | 2145 | 0.6344          | 0.6308            | 0.6279   |
| 1.1125        | 14.0  | 2310 | 0.6716          | 0.6598            | 0.6507   |
| 1.0532        | 15.0  | 2475 | 0.7006          | 0.6501            | 0.5548   |
| 1.0158        | 16.0  | 2640 | 0.6975          | 0.6445            | 0.6050   |
| 0.9504        | 17.0  | 2805 | 0.8028          | 0.5960            | 0.5457   |


### Framework versions

- PEFT 0.14.0
- Transformers 4.48.1
- Pytorch 2.1.0
- Datasets 3.2.0
- Tokenizers 0.21.0