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t5-small-herblabels
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4823
- Rouge1: 3.0759
- Rouge2: 1.0495
- Rougel: 3.0758
- Rougelsum: 3.0431
- Gen Len: 18.9716
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 | 264 | 1.6010 | 2.4276 | 0.5658 | 2.3546 | 2.3099 | 18.9091 |
| 2.5052 | 2.0 | 528 | 1.0237 | 2.9016 | 0.3395 | 2.8221 | 2.783 | 18.9673 |
| 2.5052 | 3.0 | 792 | 0.7793 | 2.962 | 0.3091 | 2.9375 | 2.8786 | 18.9588 |
| 1.1552 | 4.0 | 1056 | 0.6530 | 2.98 | 0.4375 | 2.9584 | 2.8711 | 18.9588 |
| 1.1552 | 5.0 | 1320 | 0.5863 | 3.0023 | 0.5882 | 2.987 | 2.9155 | 18.9588 |
| 0.8659 | 6.0 | 1584 | 0.5428 | 3.0576 | 0.8019 | 3.0494 | 2.9989 | 18.9716 |
| 0.8659 | 7.0 | 1848 | 0.5145 | 3.0808 | 0.9476 | 3.0719 | 3.0237 | 18.9716 |
| 0.747 | 8.0 | 2112 | 0.4962 | 3.0748 | 1.0032 | 3.0683 | 3.0359 | 18.9716 |
| 0.747 | 9.0 | 2376 | 0.4856 | 3.0702 | 1.0196 | 3.0665 | 3.0328 | 18.9716 |
| 0.6987 | 10.0 | 2640 | 0.4823 | 3.0759 | 1.0495 | 3.0758 | 3.0431 | 18.9716 |
Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0
- Datasets 1.16.1
- Tokenizers 0.10.3
