olonok_billsum_model
This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8641
- Rouge1: 0.2024
- Rouge2: 0.1156
- Rougel: 0.177
- Rougelsum: 0.177
- 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 | 2.0236 | 0.1683 | 0.0807 | 0.1445 | 0.1449 | 19.0 |
No log | 2.0 | 124 | 1.9080 | 0.2041 | 0.1158 | 0.1778 | 0.1779 | 19.0 |
No log | 3.0 | 186 | 1.8728 | 0.2024 | 0.1165 | 0.1778 | 0.1776 | 19.0 |
No log | 4.0 | 248 | 1.8641 | 0.2024 | 0.1156 | 0.177 | 0.177 | 19.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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