bart-large-cnn-finetuned-xsum
This model is a fine-tuned version of facebook/bart-large-cnn on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6326
- Rouge1: 46.6416
- Rouge2: 17.5341
- Rougel: 27.7134
- Rougelsum: 42.3332
- Gen Len: 135.9615
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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 21 | 1.6566 | 46.2086 | 17.2665 | 26.9931 | 41.4081 | 132.9423 |
| No log | 2.0 | 42 | 1.6262 | 47.1941 | 18.0513 | 28.3194 | 42.2051 | 138.5192 |
| No log | 3.0 | 63 | 1.6326 | 46.6416 | 17.5341 | 27.7134 | 42.3332 | 135.9615 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
facebook/bart-large-cnn