my_awesome_billsum_model
This model is a fine-tuned version of t5-small on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.5092
- Rouge1: 0.1486
- Rouge2: 0.0551
- Rougel: 0.123
- Rougelsum: 0.1226
- 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: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 62 | 2.7960 | 0.131 | 0.0394 | 0.1101 | 0.1099 | 19.0 |
No log | 2.0 | 124 | 2.5857 | 0.1389 | 0.0502 | 0.1167 | 0.1162 | 19.0 |
No log | 3.0 | 186 | 2.5245 | 0.1462 | 0.054 | 0.1217 | 0.1215 | 19.0 |
No log | 4.0 | 248 | 2.5092 | 0.1486 | 0.0551 | 0.123 | 0.1226 | 19.0 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
- Downloads last month
- 10
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.