---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5_medical_diagnostic_peft
  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. -->

# t5_medical_diagnostic_peft

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7468
- Rouge1: 0.4227
- Rouge2: 0.2234
- Rougel: 0.3594
- Rougelsum: 0.3595
- Gen Len: 17.5843

## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.9974        | 0.2   | 500  | 1.7864          | 0.4167 | 0.221  | 0.3561 | 0.356     | 17.6092 |
| 1.9244        | 0.4   | 1000 | 1.7504          | 0.4166 | 0.2214 | 0.3577 | 0.3577    | 16.9937 |
| 1.9121        | 0.6   | 1500 | 1.7274          | 0.4209 | 0.2245 | 0.3593 | 0.3594    | 17.2876 |
| 1.8677        | 0.8   | 2000 | 1.7101          | 0.4253 | 0.2266 | 0.363  | 0.3631    | 17.5681 |
| 1.8927        | 1.0   | 2500 | 1.7468          | 0.4227 | 0.2234 | 0.3594 | 0.3595    | 17.5843 |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1