multi_summarize
This model is a fine-tuned version of google-t5/t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.9849
- Rouge1: 0.0883
- Rouge2: 0.0266
- Rougel: 0.0685
- Rougelsum: 0.0685
- Gen Len: 18.9808
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: 2
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 496 | 3.0124 | 0.0865 | 0.0259 | 0.0672 | 0.0672 | 18.8085 |
3.391 | 2.0 | 992 | 2.9849 | 0.0883 | 0.0266 | 0.0685 | 0.0685 | 18.9808 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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