keyword-summarizer-10000-v1
This model is a fine-tuned version of google/flan-t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0126
- Rouge1: 0.7499
- Rouge2: 0.6775
- Rougel: 0.7490
- Rougelsum: 0.7488
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: 0.0003
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 0.1198 | 1.0 | 873 | 0.0264 | 0.7472 | 0.6686 | 0.7455 | 0.7453 |
| 0.0297 | 2.0 | 1746 | 0.0133 | 0.7495 | 0.6764 | 0.7489 | 0.7487 |
| 0.0113 | 3.0 | 2619 | 0.0143 | 0.7497 | 0.6744 | 0.7476 | 0.7474 |
| 0.0076 | 4.0 | 3492 | 0.0126 | 0.7499 | 0.6775 | 0.7490 | 0.7488 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
google/flan-t5-base