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--- |
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license: apache-2.0 |
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base_model: tohoku-nlp/bert-base-japanese-v3 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: gigazine-labeling |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# gigazine-labeling |
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This model is a fine-tuned version of [tohoku-nlp/bert-base-japanese-v3](https://huggingface.co./tohoku-nlp/bert-base-japanese-v3) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3062 |
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- Accuracy: 0.623 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 2.4089 | 1.0 | 125 | 1.5892 | 0.551 | |
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| 1.2661 | 2.0 | 250 | 1.3291 | 0.601 | |
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| 0.6811 | 3.0 | 375 | 1.3062 | 0.623 | |
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### Framework versions |
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- Transformers 4.43.4 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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