<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
t5-small-finetuned-summarization-cnn-ver2
This model is a fine-tuned version of t5-small on the cnn_dailymail dataset. It achieves the following results on the evaluation set:
- Loss: 2.0084
- Bertscore-mean-precision: 0.8859
- Bertscore-mean-recall: 0.8592
- Bertscore-mean-f1: 0.8721
- Bertscore-median-precision: 0.8855
- Bertscore-median-recall: 0.8578
- Bertscore-median-f1: 0.8718
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: 5e-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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Bertscore-mean-precision | Bertscore-mean-recall | Bertscore-mean-f1 | Bertscore-median-precision | Bertscore-median-recall | Bertscore-median-f1 |
---|---|---|---|---|---|---|---|---|---|
2.0422 | 1.0 | 718 | 2.0139 | 0.8853 | 0.8589 | 0.8717 | 0.8857 | 0.8564 | 0.8715 |
1.9481 | 2.0 | 1436 | 2.0085 | 0.8863 | 0.8591 | 0.8723 | 0.8858 | 0.8577 | 0.8718 |
1.9231 | 3.0 | 2154 | 2.0084 | 0.8859 | 0.8592 | 0.8721 | 0.8855 | 0.8578 | 0.8718 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.0
- Tokenizers 0.13.2