---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-medical_transcription
  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-small-medical_transcription

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7744
- Rouge1: 0.3722
- Rouge2: 0.2709
- Rougel: 0.3628
- Rougelsum: 0.3619
- Gen Len: 17.0877

## 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.4475        | 1.0   | 27   | 2.0647          | 0.3288 | 0.2503 | 0.3252 | 0.3212    | 17.2281 |
| 2.0319        | 2.0   | 54   | 1.9089          | 0.3456 | 0.2527 | 0.3407 | 0.3377    | 16.3684 |
| 1.8772        | 3.0   | 81   | 1.8572          | 0.3528 | 0.2615 | 0.3478 | 0.3457    | 16.1579 |
| 1.796         | 4.0   | 108  | 1.8211          | 0.3274 | 0.2479 | 0.324  | 0.3216    | 15.7719 |
| 1.7107        | 5.0   | 135  | 1.7972          | 0.3689 | 0.277  | 0.3614 | 0.3586    | 16.3509 |
| 1.711         | 6.0   | 162  | 1.7852          | 0.359  | 0.2599 | 0.3505 | 0.348     | 16.2105 |
| 1.7581        | 7.0   | 189  | 1.7773          | 0.3659 | 0.2646 | 0.3566 | 0.3559    | 16.9298 |
| 1.704         | 8.0   | 216  | 1.7744          | 0.3722 | 0.2709 | 0.3628 | 0.3619    | 17.0877 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2