bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization-finetuned-xsum
This model is a fine-tuned version of mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization on the xsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.9401
- Rouge1: 24.9094
- Rouge2: 7.3754
- Rougel: 18.2282
- Rougelsum: 18.9508
- Gen Len: 61.4478
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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 3.0991 | 1.0 | 12753 | 2.9401 | 24.9094 | 7.3754 | 18.2282 | 18.9508 | 61.4478 |
Framework versions
- Transformers 4.30.0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.13.3
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