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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: google-bert/bert-base-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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model-index: |
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- name: intent_classfication2 |
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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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# intent_classfication2 |
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1321 |
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- Accuracy: 0.9618 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 15 |
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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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| 1.6215 | 1.0 | 655 | 1.0384 | 0.8342 | |
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| 1.0518 | 2.0 | 1310 | 0.5333 | 0.8892 | |
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| 0.676 | 3.0 | 1965 | 0.3383 | 0.9228 | |
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| 0.3837 | 4.0 | 2620 | 0.2589 | 0.9373 | |
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| 0.3307 | 5.0 | 3275 | 0.2148 | 0.9415 | |
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| 0.2926 | 6.0 | 3930 | 0.1872 | 0.9492 | |
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| 0.2465 | 7.0 | 4585 | 0.1698 | 0.9530 | |
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| 0.2338 | 8.0 | 5240 | 0.1585 | 0.9553 | |
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| 0.2156 | 9.0 | 5895 | 0.1486 | 0.9599 | |
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| 0.2078 | 10.0 | 6550 | 0.1429 | 0.9603 | |
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| 0.2 | 11.0 | 7205 | 0.1392 | 0.9603 | |
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| 0.1973 | 12.0 | 7860 | 0.1362 | 0.9614 | |
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| 0.184 | 13.0 | 8515 | 0.1339 | 0.9622 | |
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| 0.1884 | 14.0 | 9170 | 0.1326 | 0.9622 | |
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| 0.1871 | 15.0 | 9825 | 0.1321 | 0.9618 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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