---
base_model: StanfordAIMI/RadPhi-2
tags:
- generated_from_trainer
model-index:
- name: outputs_20240325
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# outputs_20240325

This model is a fine-tuned version of [StanfordAIMI/RadPhi-2](https://huggingface.co/StanfordAIMI/RadPhi-2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0816

## 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: 12.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1831        | 0.64  | 25   | 0.1257          |
| 0.1239        | 1.28  | 50   | 0.1044          |
| 0.108         | 1.92  | 75   | 0.0995          |
| 0.0976        | 2.56  | 100  | 0.0978          |
| 0.094         | 3.2   | 125  | 0.0886          |
| 0.0828        | 3.84  | 150  | 0.0893          |
| 0.078         | 4.48  | 175  | 0.0907          |
| 0.0767        | 5.12  | 200  | 0.0866          |
| 0.0697        | 5.76  | 225  | 0.0840          |
| 0.0646        | 6.39  | 250  | 0.0819          |
| 0.0594        | 7.03  | 275  | 0.0795          |
| 0.052         | 7.67  | 300  | 0.0795          |
| 0.0478        | 8.31  | 325  | 0.0803          |
| 0.0447        | 8.95  | 350  | 0.0786          |
| 0.0392        | 9.59  | 375  | 0.0800          |
| 0.038         | 10.23 | 400  | 0.0813          |
| 0.0357        | 10.87 | 425  | 0.0810          |
| 0.035         | 11.51 | 450  | 0.0816          |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2