bart-base-vn-re-attention-vn-tokenizer
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: 2.4481
- Rouge1: 18.0845
- Rouge2: 8.2722
- Rougel: 15.4154
- Rougelsum: 16.6591
- Bleu-1: 0.0007
- Bleu-2: 0.0004
- Bleu-3: 0.0002
- Bleu-4: 0.0001
- Gen Len: 19.811
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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu-1 | Bleu-2 | Bleu-3 | Bleu-4 | Gen Len |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2.6584 | 1.0 | 10886 | 2.4481 | 18.0845 | 8.2722 | 15.4154 | 16.6591 | 0.0007 | 0.0004 | 0.0002 | 0.0001 | 19.811 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1
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Base model
facebook/bart-base