metadata
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: final_bart_prepro_fix
results: []
final_bart_prepro_fix
This model is a fine-tuned version of gogamza/kobart-base-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.6100
- Rouge1: 35.5593
- Rouge2: 13.0497
- Rougel: 23.5672
- Bleu1: 29.5206
- Bleu2: 17.3914
- Bleu3: 10.5577
- Bleu4: 6.1502
- Rdass: 0.6449
- Gen Len: 49.7389
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: 3e-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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Bleu1 | Bleu2 | Bleu3 | Bleu4 | Rdass | Gen Len |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2.1622 | 1.51 | 1000 | 2.6687 | 35.4366 | 12.8631 | 23.1588 | 29.4018 | 17.2004 | 10.3744 | 6.052 | 0.6379 | 49.4266 |
| 2.0114 | 3.02 | 2000 | 2.6090 | 35.1436 | 13.0347 | 23.4682 | 28.8917 | 17.0965 | 10.1873 | 5.896 | 0.6389 | 46.1096 |
| 1.8758 | 4.53 | 3000 | 2.6100 | 35.5593 | 13.0497 | 23.5672 | 29.5206 | 17.3914 | 10.5577 | 6.1502 | 0.6449 | 49.7389 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2