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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- banking77 |
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metrics: |
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- accuracy |
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model-index: |
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- name: banking-intent-distilbert-classifier |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: banking77 |
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type: banking77 |
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config: default |
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split: test |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.925 |
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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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# banking-intent-distilbert-classifier |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the banking77 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3307 |
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- Accuracy: 0.925 |
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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-06 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 10 |
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- mixed_precision_training: Native AMP |
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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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| 0.0124 | 1.0 | 313 | 0.3307 | 0.925 | |
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| 0.0102 | 2.0 | 626 | 0.3331 | 0.9289 | |
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| 0.0077 | 3.0 | 939 | 0.3381 | 0.9282 | |
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| 0.0062 | 4.0 | 1252 | 0.3406 | 0.9276 | |
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| 0.0059 | 5.0 | 1565 | 0.3423 | 0.9282 | |
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| 0.0045 | 6.0 | 1878 | 0.3445 | 0.9282 | |
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| 0.0046 | 7.0 | 2191 | 0.3458 | 0.9286 | |
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| 0.0041 | 8.0 | 2504 | 0.3470 | 0.9286 | |
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| 0.0038 | 9.0 | 2817 | 0.3472 | 0.9286 | |
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| 0.0034 | 10.0 | 3130 | 0.3475 | 0.9286 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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