---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: medical_diagnostic_summarizer
  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. -->

# medical_diagnostic_summarizer

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1099
- Rouge1: 0.398
- Rouge2: 0.2035
- Rougel: 0.3373
- Rougelsum: 0.3373
- Gen Len: 17.8606

## 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: 2e-05
- 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.4288        | 1.0   | 2500  | 2.1944          | 0.3895 | 0.1972 | 0.3304 | 0.3303    | 17.8459 |
| 2.3376        | 2.0   | 5000  | 2.1381          | 0.3948 | 0.2012 | 0.3347 | 0.3347    | 17.8277 |
| 2.2978        | 3.0   | 7500  | 2.1155          | 0.3972 | 0.2027 | 0.3365 | 0.3366    | 17.8694 |
| 2.3072        | 4.0   | 10000 | 2.1099          | 0.398  | 0.2035 | 0.3373 | 0.3373    | 17.8606 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3