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t5-large-new-v1
This model is a fine-tuned version of t5-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1352
- Rouge2 Precision: 0.7349
- Rouge2 Recall: 0.0736
- Rouge2 Fmeasure: 0.1318
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: 5e-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: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
---|---|---|---|---|---|---|
0.031 | 1.0 | 2000 | 0.1570 | 0.7141 | 0.0725 | 0.1298 |
0.022 | 2.0 | 4000 | 0.1339 | 0.7571 | 0.0751 | 0.1349 |
0.0191 | 3.0 | 6000 | 0.1333 | 0.76 | 0.077 | 0.138 |
0.0163 | 4.0 | 8000 | 0.1304 | 0.7413 | 0.0752 | 0.1343 |
0.0158 | 5.0 | 10000 | 0.1241 | 0.7372 | 0.0733 | 0.1311 |
0.0138 | 6.0 | 12000 | 0.1343 | 0.7486 | 0.0734 | 0.1317 |
0.0132 | 7.0 | 14000 | 0.1318 | 0.7232 | 0.0721 | 0.129 |
0.0122 | 8.0 | 16000 | 0.1352 | 0.7349 | 0.0736 | 0.1318 |
Framework versions
- Transformers 4.27.3
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.2