results
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2057
- Rouge2 Precision: 0.3564
- Rouge2 Recall: 0.2124
- Rouge2 Fmeasure: 0.256
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| No log | 1.0 | 240 | 0.3146 | 0.2121 | 0.1134 | 0.1424 |
| No log | 2.0 | 480 | 0.2444 | 0.2855 | 0.1519 | 0.19 |
| 0.6451 | 3.0 | 720 | 0.2195 | 0.3225 | 0.1821 | 0.223 |
| 0.6451 | 4.0 | 960 | 0.2078 | 0.355 | 0.2113 | 0.2548 |
| 0.2978 | 5.0 | 1200 | 0.2057 | 0.3564 | 0.2124 | 0.256 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cpu
- Datasets 2.4.0
- Tokenizers 0.12.1
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