t5-base-billsum
This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6188
- Rouge1: 24.2144
- Rouge2: 19.5091
- Rougel: 23.4392
- Rougelsum: 23.6056
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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 1.9236 | 1.0 | 1185 | 1.5895 | 24.1667 | 19.4242 | 23.3539 | 23.5422 |
| 1.7231 | 2.0 | 2370 | 1.5380 | 24.4655 | 19.8009 | 23.6777 | 23.8703 |
| 1.6708 | 3.0 | 3555 | 1.5187 | 24.4628 | 19.816 | 23.6919 | 23.887 |
| 1.7884 | 4.0 | 4740 | 1.6197 | 24.2271 | 19.5246 | 23.4512 | 23.6138 |
| 1.8212 | 5.0 | 5925 | 1.6188 | 24.2144 | 19.5091 | 23.4392 | 23.6056 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Model tree for antonkurylo/t5-base-X-billsum
Base model
google-t5/t5-base