t5-large-finetuned
This model is a fine-tuned version of google-t5/t5-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6085
- Rouge1: 25.8315
- Rouge2: 11.4547
- Rougel: 22.5227
- Rougelsum: 22.7341
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: 5.6e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 1.7803 | 1.0 | 5351 | 1.6070 | 25.1375 | 10.9135 | 21.8817 | 22.0576 |
| 1.4798 | 2.0 | 10702 | 1.4737 | 25.4328 | 11.0728 | 21.8859 | 22.0964 |
| 1.2923 | 3.0 | 16053 | 1.4838 | 25.6553 | 11.3169 | 22.1861 | 22.3694 |
| 1.1509 | 4.0 | 21404 | 1.4842 | 25.7181 | 11.4215 | 22.271 | 22.4394 |
| 1.0404 | 5.0 | 26755 | 1.5121 | 26.0812 | 11.8877 | 22.7516 | 22.941 |
| 0.9533 | 6.0 | 32106 | 1.5602 | 25.5218 | 11.486 | 22.2236 | 22.4401 |
| 0.888 | 7.0 | 37457 | 1.5832 | 25.8289 | 11.5647 | 22.5507 | 22.7091 |
| 0.8424 | 8.0 | 42808 | 1.6085 | 25.8315 | 11.4547 | 22.5227 | 22.7341 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
google-t5/t5-large