---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned_BBC
  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. -->

# mt5-small-finetuned_BBC

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7853
- Rouge1: 0.2188
- Rouge2: 0.1377
- Rougel: 0.1944
- Rougelsum: 0.1972

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 1.8481        | 1.0   | 223  | 0.9611          | 0.1966 | 0.1275 | 0.1759 | 0.1776    |
| 1.4347        | 2.0   | 446  | 0.8815          | 0.2065 | 0.1199 | 0.1805 | 0.1837    |
| 1.2585        | 3.0   | 669  | 0.8541          | 0.2129 | 0.1291 | 0.1880 | 0.1911    |
| 1.192         | 4.0   | 892  | 0.8184          | 0.2149 | 0.1320 | 0.1893 | 0.1926    |
| 1.1084        | 5.0   | 1115 | 0.8102          | 0.2156 | 0.1333 | 0.1908 | 0.1938    |
| 1.0796        | 6.0   | 1338 | 0.7937          | 0.2168 | 0.1337 | 0.1913 | 0.1944    |
| 1.0657        | 7.0   | 1561 | 0.7933          | 0.2181 | 0.1370 | 0.1939 | 0.1967    |
| 1.0488        | 8.0   | 1784 | 0.7853          | 0.2188 | 0.1377 | 0.1944 | 0.1972    |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0
- Datasets 2.20.0
- Tokenizers 0.19.1