my_text_summarization_model
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.3919
- Rouge1: 0.1518
- Rouge2: 0.0605
- Rougel: 0.1256
- Rougelsum: 0.126
- Gen Len: 19.0
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: 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: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 62 | 2.5162 | 0.133 | 0.0432 | 0.1104 | 0.1106 | 19.0 |
No log | 2.0 | 124 | 2.4373 | 0.139 | 0.0484 | 0.1143 | 0.1144 | 19.0 |
No log | 3.0 | 186 | 2.4020 | 0.1459 | 0.0557 | 0.1212 | 0.1215 | 19.0 |
No log | 4.0 | 248 | 2.3919 | 0.1518 | 0.0605 | 0.1256 | 0.126 | 19.0 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
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