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license: apache-2.0 |
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base_model: google-bert/bert-large-cased-whole-word-masking |
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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: Intent-classification-BERT-Large-Ashuv5 |
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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-classification-BERT-Large-Ashuv5 |
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This model is a fine-tuned version of [google-bert/bert-large-cased-whole-word-masking](https://huggingface.co./google-bert/bert-large-cased-whole-word-masking) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7988 |
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- Accuracy: 0.1420 |
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- F1: 0.0414 |
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- Precision: 0.0237 |
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- Recall: 0.1667 |
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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: 0.0005 |
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- train_batch_size: 16 |
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- eval_batch_size: 32 |
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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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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 2.1123 | 0.24 | 10 | 1.8066 | 0.2174 | 0.0595 | 0.0362 | 0.1667 | |
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| 1.8577 | 0.49 | 20 | 1.9500 | 0.1242 | 0.0368 | 0.0207 | 0.1667 | |
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| 1.8864 | 0.73 | 30 | 1.7999 | 0.1801 | 0.0509 | 0.0300 | 0.1667 | |
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| 1.8516 | 0.98 | 40 | 1.8570 | 0.1429 | 0.0417 | 0.0238 | 0.1667 | |
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| 1.8664 | 1.22 | 50 | 1.8667 | 0.1242 | 0.0368 | 0.0207 | 0.1667 | |
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| 1.8207 | 1.46 | 60 | 1.9616 | 0.1180 | 0.0352 | 0.0197 | 0.1667 | |
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| 1.8652 | 1.71 | 70 | 1.7831 | 0.2174 | 0.0595 | 0.0362 | 0.1667 | |
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| 1.8372 | 1.95 | 80 | 1.8018 | 0.2174 | 0.0595 | 0.0362 | 0.1667 | |
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| 1.8671 | 2.2 | 90 | 1.8436 | 0.1180 | 0.0352 | 0.0197 | 0.1667 | |
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| 1.8484 | 2.44 | 100 | 1.7722 | 0.2174 | 0.0595 | 0.0362 | 0.1667 | |
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| 1.8262 | 2.68 | 110 | 1.7752 | 0.2174 | 0.0595 | 0.0362 | 0.1667 | |
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| 1.8292 | 2.93 | 120 | 1.8064 | 0.1242 | 0.0368 | 0.0207 | 0.1667 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.2 |
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