<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
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: 2.5293
- Rouge1: 0.1494
- Rouge2: 0.0571
- Rougel: 0.124
- Rougelsum: 0.1237
- 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 | 2.8266 | 0.1259 | 0.0355 | 0.106 | 0.106 | 19.0 |
No log | 2.0 | 124 | 2.6125 | 0.1364 | 0.0479 | 0.1147 | 0.1149 | 19.0 |
No log | 3.0 | 186 | 2.5473 | 0.1456 | 0.0536 | 0.1213 | 0.121 | 19.0 |
No log | 4.0 | 248 | 2.5293 | 0.1494 | 0.0571 | 0.124 | 0.1237 | 19.0 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3