T5_small_title
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.4558
- Rouge1: 0.316
- Rouge2: 0.1498
- Rougel: 0.2735
- Rougelsum: 0.2728
- Gen Len: 16.495
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 100 | 2.8637 | 0.2464 | 0.093 | 0.207 | 0.2066 | 18.87 |
| No log | 2.0 | 200 | 2.6086 | 0.2702 | 0.1142 | 0.2303 | 0.2299 | 18.475 |
| No log | 3.0 | 300 | 2.5391 | 0.2943 | 0.1373 | 0.2572 | 0.2565 | 17.44 |
| No log | 4.0 | 400 | 2.5082 | 0.2997 | 0.1421 | 0.2636 | 0.2629 | 17.02 |
| 2.8756 | 5.0 | 500 | 2.4853 | 0.3111 | 0.145 | 0.271 | 0.2701 | 16.755 |
| 2.8756 | 6.0 | 600 | 2.4729 | 0.3165 | 0.1501 | 0.2753 | 0.2745 | 16.555 |
| 2.8756 | 7.0 | 700 | 2.4635 | 0.3215 | 0.1533 | 0.2771 | 0.2768 | 16.51 |
| 2.8756 | 8.0 | 800 | 2.4601 | 0.3224 | 0.154 | 0.2773 | 0.2776 | 16.38 |
| 2.8756 | 9.0 | 900 | 2.4569 | 0.3167 | 0.1505 | 0.274 | 0.2733 | 16.495 |
| 2.5758 | 10.0 | 1000 | 2.4558 | 0.316 | 0.1498 | 0.2735 | 0.2728 | 16.495 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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Base model
google-t5/t5-small