---
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: MI_Legislature_Summarizer
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# MI_Legislature_Summarizer

This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9612
- Rouge1: 0.4533
- Rouge2: 0.3207
- Rougel: 0.4327
- Rougelsum: 0.4326
- Gen Len: 19.6377

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.383         | 1.0   | 7240  | 1.1655          | 0.431  | 0.2961 | 0.4104 | 0.4103    | 19.6311 |
| 1.2296        | 2.0   | 14480 | 1.0504          | 0.4454 | 0.3136 | 0.4262 | 0.426     | 19.6413 |
| 1.1182        | 3.0   | 21720 | 0.9941          | 0.4503 | 0.3176 | 0.4303 | 0.4302    | 19.6399 |
| 1.1077        | 4.0   | 28960 | 0.9694          | 0.4533 | 0.3205 | 0.4328 | 0.4327    | 19.6358 |
| 1.0961        | 5.0   | 36200 | 0.9612          | 0.4533 | 0.3207 | 0.4327 | 0.4326    | 19.6377 |


### Framework versions

- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1