metadata
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: FL_Legislature_Summarizer
results: []
FL_Legislature_Summarizer
This model is a fine-tuned version of google-t5/t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3128
- Rouge1: 0.6498
- Rouge2: 0.6141
- Rougel: 0.6438
- Rougelsum: 0.644
- Gen Len: 19.5408
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: 0.0002
- 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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.4196 | 1.0 | 2095 | 0.3458 | 0.6444 | 0.6051 | 0.6381 | 0.6382 | 19.5489 |
| 0.2907 | 2.0 | 4190 | 0.3141 | 0.6498 | 0.6124 | 0.6437 | 0.644 | 19.5403 |
| 0.2901 | 3.0 | 6285 | 0.3128 | 0.6498 | 0.6141 | 0.6438 | 0.644 | 19.5408 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1