theus_concepttagger
This model is a fine-tuned version of facebook/bart-large-cnn on the xsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.6249
- Rouge1: 34.8663
- Rouge2: 15.1526
- Rougel: 26.1224
- Rougelsum: 26.5164
- Gen Len: 62.4475
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 |
|---|---|---|---|---|---|---|---|---|
| 1.4096 | 1.0 | 12753 | 1.6249 | 34.8663 | 15.1526 | 26.1224 | 26.5164 | 62.4475 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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facebook/bart-large-cnnDataset used to train namanpundir/theus_concepttagger
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Evaluation results
- Rouge1 on xsumvalidation set self-reported34.866