kobart-hashtag / README.md
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---
license: mit
tags:
- kobart-hashtag
- generated_from_trainer
base_model: gogamza/kobart-base-v2
model-index:
- name: modelling
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# modelling
This model is a fine-tuned version of [gogamza/kobart-base-v2](https://huggingface.co./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