metadata
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: my_billsum_model
results: []
my_billsum_model
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.5803
- Rouge1: 0.1414
- Rouge2: 0.0501
- Rougel: 0.1176
- Rougelsum: 0.1176
- 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
- training_steps: 200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 3.9137 | 0.65 | 40 | 3.0404 | 0.1351 | 0.044 | 0.1138 | 0.114 | 19.0 |
| 3.0852 | 1.29 | 80 | 2.7349 | 0.1363 | 0.0453 | 0.1143 | 0.1144 | 19.0 |
| 2.9298 | 1.94 | 120 | 2.6341 | 0.1405 | 0.0471 | 0.1162 | 0.1164 | 19.0 |
| 2.8389 | 2.58 | 160 | 2.5929 | 0.1413 | 0.049 | 0.1176 | 0.118 | 19.0 |
| 2.8414 | 3.23 | 200 | 2.5803 | 0.1414 | 0.0501 | 0.1176 | 0.1176 | 19.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1