t5_billsum_model
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: 2.6878
- Rouge1: 0.1347
- Rouge2: 0.0445
- Rougel: 0.1138
- Rougelsum: 0.1138
- 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 31 | 3.1584 | 0.1359 | 0.0442 | 0.1156 | 0.1155 | 19.0 |
| No log | 2.0 | 62 | 2.8302 | 0.1315 | 0.0407 | 0.111 | 0.1112 | 19.0 |
| No log | 3.0 | 93 | 2.7160 | 0.133 | 0.0426 | 0.1129 | 0.1127 | 19.0 |
| No log | 4.0 | 124 | 2.6878 | 0.1347 | 0.0445 | 0.1138 | 0.1138 | 19.0 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.2.1+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
- Downloads last month
- -
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
🙋
Ask for provider support
Model tree for geshijoker/t5_billsum_model
Base model
google-t5/t5-small