Jeolla_model
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: 0.0117
- Bleu: 88.9408
- Gen Len: 14.085
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: 32
- eval_batch_size: 32
- 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 | Bleu | Gen Len |
---|---|---|---|---|---|
0.015 | 1.0 | 15477 | 0.0136 | 88.803 | 14.0811 |
0.0111 | 2.0 | 30954 | 0.0122 | 88.8626 | 14.0804 |
0.0094 | 3.0 | 46431 | 0.0117 | 88.9408 | 14.085 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
- Downloads last month
- 111
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
Model tree for yomilimi/Jeolla_model
Base model
gogamza/kobart-base-v2