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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: bert-base-multilingual-uncased |
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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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- precision |
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- f1 |
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model-index: |
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- name: tool-bert |
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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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# tool-bert |
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This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0027 |
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- Accuracy: 1.0 |
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- Precision: 1.0 |
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- F1: 1.0 |
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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: 2e-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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:| |
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| 1.2148 | 1.0 | 50 | 1.0773 | 0.7327 | 0.8210 | 0.7354 | |
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| 0.2475 | 2.0 | 100 | 0.1127 | 0.9802 | 0.9807 | 0.9802 | |
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| 0.1395 | 3.0 | 150 | 0.0373 | 0.9901 | 0.9906 | 0.9901 | |
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| 0.009 | 4.0 | 200 | 0.0066 | 1.0 | 1.0 | 1.0 | |
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| 0.0057 | 5.0 | 250 | 0.0051 | 1.0 | 1.0 | 1.0 | |
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| 0.0044 | 6.0 | 300 | 0.0037 | 1.0 | 1.0 | 1.0 | |
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| 0.0038 | 7.0 | 350 | 0.0032 | 1.0 | 1.0 | 1.0 | |
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| 0.0035 | 8.0 | 400 | 0.0029 | 1.0 | 1.0 | 1.0 | |
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| 0.0032 | 9.0 | 450 | 0.0027 | 1.0 | 1.0 | 1.0 | |
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| 0.0032 | 10.0 | 500 | 0.0027 | 1.0 | 1.0 | 1.0 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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