---
license: llama2
base_model: StanfordAIMI/RadLLaMA-7b
tags:
- generated_from_trainer
model-index:
- name: RewardRadLLaMA-7b
  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. -->

# StanfordAIMI/RewardRadLLaMA-7b

This model is a fine-tuned version of [StanfordAIMI/RadLLaMA-7b](https://huggingface.co/StanfordAIMI/RadLLaMA-7b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0644

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 32
- total_train_batch_size: 2048
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.2634        | 0.64  | 25   | 0.2924          |
| 0.1216        | 1.28  | 50   | 0.0898          |
| 0.0833        | 1.92  | 75   | 0.0718          |
| 0.062         | 2.56  | 100  | 0.0644          |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1