metadata
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: kobart_32_6e-5_datav2_min30_lp5.0_temperature1.0
results: []
kobart_32_6e-5_datav2_min30_lp5.0_temperature1.0
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: 2.6110
- Rouge1: 35.8879
- Rouge2: 12.9302
- Rougel: 23.7819
- Bleu1: 30.0048
- Bleu2: 17.5297
- Bleu3: 10.3153
- Bleu4: 5.9092
- Gen Len: 50.8508
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: 6e-05
- train_batch_size: 32
- eval_batch_size: 128
- 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 | Gen Len |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.5664 | 3.78 | 5000 | 2.6110 | 35.8879 | 12.9302 | 23.7819 | 30.0048 | 17.5297 | 10.3153 | 5.9092 | 50.8508 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2