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finetuning-summarization-model
This model is a fine-tuned version of google/mt5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3028
- Rouge1: 29.1184
- Rouge2: 21.1309
- Rougel: 28.3412
- Rougelsum: 28.4871
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 |
|---|---|---|---|---|---|---|---|
| 6.821 | 1.0 | 450 | 1.7464 | 31.7328 | 21.1788 | 30.3949 | 30.5202 |
| 2.1307 | 2.0 | 900 | 1.4939 | 31.3208 | 22.0215 | 30.2589 | 30.3872 |
| 1.7915 | 3.0 | 1350 | 1.4322 | 28.7824 | 19.472 | 27.926 | 28.2177 |
| 1.6186 | 4.0 | 1800 | 1.3830 | 29.2568 | 20.6076 | 28.4825 | 28.6486 |
| 1.5148 | 5.0 | 2250 | 1.3504 | 29.308 | 21.0698 | 28.4755 | 28.6885 |
| 1.427 | 6.0 | 2700 | 1.3177 | 29.0294 | 20.706 | 28.271 | 28.3385 |
| 1.3793 | 7.0 | 3150 | 1.3172 | 28.9276 | 20.922 | 28.1795 | 28.3241 |
| 1.3536 | 8.0 | 3600 | 1.3028 | 29.1184 | 21.1309 | 28.3412 | 28.4871 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
