metadata
license: apache-2.0
base_model: google-t5/t5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-finetuned-billsum
results: []
t5-small-finetuned-billsum
This model is a fine-tuned version of google-t5/t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.5533
- Rouge1: 0.1356
- Rouge2: 0.0495
- Rougel: 0.1144
- Rougelsum: 0.1144
- Gen Len: 19.0
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 62 | 2.6711 | 0.1308 | 0.0445 | 0.1107 | 0.1109 | 19.0 |
| No log | 2.0 | 124 | 2.5761 | 0.1338 | 0.0483 | 0.1137 | 0.1137 | 19.0 |
| No log | 3.0 | 186 | 2.5533 | 0.1356 | 0.0495 | 0.1144 | 0.1144 | 19.0 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1