metadata
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- cnn_dailymail
model-index:
- name: t5-base-finetuned-summarization-cnn-ver2
results: []
t5-base-finetuned-summarization-cnn-ver2
This model is a fine-tuned version of t5-base on the cnn_dailymail dataset. It achieves the following results on the evaluation set:
- Loss: 1.7601
- Bertscore-mean-precision: 0.8926
- Bertscore-mean-recall: 0.8628
- Bertscore-mean-f1: 0.8772
- Bertscore-median-precision: 0.8906
- Bertscore-median-recall: 0.8600
- Bertscore-median-f1: 0.8751
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: 1
- eval_batch_size: 1
- 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 |
|---|---|---|---|---|---|---|---|---|---|
| 1.4581 | 1.0 | 5742 | 1.6800 | 0.8904 | 0.8615 | 0.8755 | 0.8887 | 0.8597 | 0.8737 |
| 1.2356 | 2.0 | 11484 | 1.7274 | 0.8924 | 0.8626 | 0.8771 | 0.8911 | 0.8607 | 0.8753 |
| 1.1073 | 3.0 | 17226 | 1.7601 | 0.8926 | 0.8628 | 0.8772 | 0.8906 | 0.8600 | 0.8751 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2