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---
tags:
- generated_from_trainer
base_model: airesearch/wangchanberta-base-att-spm-uncased
metrics:
- accuracy
model-index:
- name: fine-tune-wangchanberta-TOG-split-headline1
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. -->
# fine-tune-wangchanberta-TOG-split-headline1
This model is a fine-tuned version of [airesearch/wangchanberta-base-att-spm-uncased](https://huggingface.co/airesearch/wangchanberta-base-att-spm-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1026
- Accuracy: 0.3876
## 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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0948 | 1.0 | 27 | 1.1114 | 0.3828 |
| 1.0961 | 2.0 | 54 | 1.1019 | 0.3828 |
| 1.0971 | 3.0 | 81 | 1.1144 | 0.3876 |
| 1.0908 | 4.0 | 108 | 1.0994 | 0.3876 |
| 1.0703 | 5.0 | 135 | 1.1032 | 0.3876 |
| 1.0711 | 6.0 | 162 | 1.1057 | 0.3828 |
| 1.0658 | 7.0 | 189 | 1.1026 | 0.3876 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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