metadata
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-base-finetuned-cnn_dailymail
results: []
bart-base-finetuned-cnn_dailymail
This model is a fine-tuned version of facebook/bart-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0437
- Rouge1: 25.3365
- Rouge2: 13.3508
- Rougel: 21.4401
- Rougelsum: 23.9107
- Bleu 1: 3.9737
- Bleu 2: 2.7698
- Bleu 3: 2.0856
- Meteor: 12.8165
- Lungime rezumat: 11.6837
- Lungime original: 48.7563
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: 5.6e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu 1 | Bleu 2 | Bleu 3 | Meteor | Lungime rezumat | Lungime original |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1.3567 | 1.0 | 896 | 1.0741 | 25.256 | 13.2616 | 21.4201 | 23.8469 | 4.0588 | 2.8245 | 2.1231 | 12.7828 | 11.7437 | 48.7563 |
1.0881 | 2.0 | 1792 | 1.0609 | 25.1093 | 13.0973 | 21.1393 | 23.6685 | 3.943 | 2.7211 | 2.0277 | 12.6304 | 11.758 | 48.7563 |
1.0172 | 3.0 | 2688 | 1.0445 | 25.2209 | 13.2134 | 21.3199 | 23.8191 | 4.0205 | 2.7985 | 2.0994 | 12.7482 | 11.751 | 48.7563 |
0.9633 | 4.0 | 3584 | 1.0392 | 25.0763 | 13.145 | 21.1885 | 23.6877 | 3.9164 | 2.7134 | 2.043 | 12.6657 | 11.6963 | 48.7563 |
0.921 | 5.0 | 4480 | 1.0369 | 25.2214 | 13.3045 | 21.4317 | 23.8493 | 3.9533 | 2.7617 | 2.0827 | 12.7434 | 11.6727 | 48.7563 |
0.8865 | 6.0 | 5376 | 1.0377 | 25.3824 | 13.4543 | 21.4896 | 24.0024 | 3.9731 | 2.799 | 2.1298 | 12.9173 | 11.6563 | 48.7563 |
0.8576 | 7.0 | 6272 | 1.0347 | 25.1748 | 13.3232 | 21.3419 | 23.7755 | 3.925 | 2.7544 | 2.089 | 12.7437 | 11.6417 | 48.7563 |
0.8353 | 8.0 | 7168 | 1.0373 | 25.3485 | 13.3938 | 21.4843 | 23.9589 | 3.9384 | 2.7462 | 2.071 | 12.8098 | 11.6407 | 48.7563 |
0.8173 | 9.0 | 8064 | 1.0448 | 25.345 | 13.3389 | 21.4394 | 23.9221 | 3.9543 | 2.7587 | 2.0827 | 12.8046 | 11.6827 | 48.7563 |
0.8044 | 10.0 | 8960 | 1.0437 | 25.3365 | 13.3508 | 21.4401 | 23.9107 | 3.9737 | 2.7698 | 2.0856 | 12.8165 | 11.6837 | 48.7563 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.2+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1