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# t5-small-finetuned-BBCNews

This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the BBC News Articles dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7321
- Rouge1: 0.1672
- Rouge2: 0.1387
- Rougel: 0.1605
- Rougelsum: 0.1622

## 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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 1.0538        | 1.0   | 344  | 0.7877          | 0.156  | 0.1219 | 0.1472 | 0.1492    |
| 0.7611        | 2.0   | 688  | 0.7479          | 0.1641 | 0.1333 | 0.1565 | 0.1577    |
| 0.7189        | 3.0   | 1032 | 0.7400          | 0.1659 | 0.1365 | 0.1589 | 0.1606    |
| 0.7021        | 4.0   | 1376 | 0.7370          | 0.1671 | 0.138  | 0.1603 | 0.1618    |
| 0.6976        | 5.0   | 1720 | 0.7321          | 0.1672 | 0.1387 | 0.1605 | 0.1622    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
{"language": ["en"], "license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "base_model": "google-t5/t5-small", "pipeline_tag": "summarization", "model-index": [{"name": "t5-small-finetuned-BBCNews", "results": []}]}
transformers tensorboard safetensors t5 text2text-generation summarization generated_from_trainer en base_model:google-t5/t5-small license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us