metadata
license: mit
base_model: gogamza/kobart-base-v2
tags:
- kobart-hashtag
- generated_from_trainer
model-index:
- name: modelling
results: []
modelling
This model is a fine-tuned version of gogamza/kobart-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7086
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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2628 | 1.23 | 500 | 0.6570 |
| 0.1678 | 2.47 | 1000 | 0.7086 |
| 0.1958 | 3.7 | 1500 | 0.7066 |
| 0.1283 | 4.94 | 2000 | 0.7354 |
| 0.0883 | 6.17 | 2500 | 0.7892 |
| 0.066 | 7.41 | 3000 | 0.8266 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.0