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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
should probably proofread and complete it, then remove this comment. -->
# 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
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