t5-base-finetuned-multi-oe-full
This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2883
- Rouge1: 59.9814
- Rouge2: 51.5747
- Rougel: 59.4429
- Rougelsum: 59.4001
- Gen Len: 10.6632
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: 0.002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.8355 | 1.0 | 591 | 0.3871 | 51.195 | 41.4443 | 50.5766 | 50.5419 | 11.04 |
| 0.3465 | 2.0 | 1182 | 0.3003 | 57.5018 | 48.6629 | 56.9622 | 56.8835 | 10.767 |
| 0.2252 | 3.0 | 1773 | 0.2883 | 59.9814 | 51.5747 | 59.4429 | 59.4001 | 10.6632 |
Framework versions
- Transformers 4.35.0
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.14.1
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Base model
google-t5/t5-base