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my_awesome_billsum_model
This model is a fine-tuned version of sorayutmild/mt5-thai-sum-finetuned-sanook-news-headlines on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 0.108
- Rouge2: 0.0
- Rougel: 0.1082
- Rougelsum: 0.1096
- Gen Len: 16.6196
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: 2e-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: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 46 | nan | 0.108 | 0.0 | 0.1082 | 0.1096 | 16.6196 |
No log | 2.0 | 92 | nan | 0.108 | 0.0 | 0.1082 | 0.1096 | 16.6196 |
No log | 3.0 | 138 | nan | 0.108 | 0.0 | 0.1082 | 0.1096 | 16.6196 |
No log | 4.0 | 184 | nan | 0.108 | 0.0 | 0.1082 | 0.1096 | 16.6196 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2