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README.md
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---
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license: apache-2.0
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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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- f1
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model-index:
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- name: distilbert-base-uncased-finetuned-banking77
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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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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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- name: F1
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type: f1
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value: 0.925018570680639
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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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# distilbert-base-uncased-finetuned-banking77
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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: 0.2935
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- Accuracy: 0.925
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- F1: 0.9250
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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: 9.686210354742596e-05
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- train_batch_size: 64
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- eval_batch_size: 32
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- seed: 40
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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: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| No log | 1.0 | 126 | 1.1457 | 0.7896 | 0.7685 |
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| No log | 2.0 | 252 | 0.4673 | 0.8906 | 0.8889 |
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| No log | 3.0 | 378 | 0.3488 | 0.9150 | 0.9151 |
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| 0.9787 | 4.0 | 504 | 0.3238 | 0.9180 | 0.9179 |
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| 0.9787 | 5.0 | 630 | 0.3126 | 0.9225 | 0.9226 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.11.0
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- Datasets 2.0.0
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- Tokenizers 0.11.6
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