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Xensword-T5-Base-Summarizer
This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.0029
- Rouge1: 0.1594
- Rouge2: 0.0664
- Rougel: 0.1405
- Rougelsum: 0.14
- 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: 8
- eval_batch_size: 8
- 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 | 157 | 2.1287 | 0.157 | 0.0654 | 0.1388 | 0.1382 | 19.0 |
No log | 2.0 | 314 | 2.0431 | 0.1613 | 0.0672 | 0.1419 | 0.1415 | 19.0 |
No log | 3.0 | 471 | 2.0179 | 0.1593 | 0.0665 | 0.1406 | 0.1401 | 19.0 |
2.2552 | 4.0 | 628 | 2.0029 | 0.1594 | 0.0664 | 0.1405 | 0.14 | 19.0 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3