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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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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: Sentiment-Analysis-on-Twitter-BCS |
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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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# Sentiment-Analysis-on-Twitter-BCS |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1303 |
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- Accuracy: 0.9615 |
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- Precision: 0.7730 |
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- Recall: 0.6384 |
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- F1: 0.6993 |
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- Roc Auc: 0.9701 |
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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: 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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:| |
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| 0.211 | 1.0 | 1798 | 0.1622 | 0.9515 | 0.6769 | 0.5893 | 0.6301 | 0.9417 | |
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| 0.1369 | 2.0 | 3596 | 0.1568 | 0.9568 | 0.7009 | 0.6696 | 0.6849 | 0.9646 | |
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| 0.1118 | 3.0 | 5394 | 0.1303 | 0.9615 | 0.7730 | 0.6384 | 0.6993 | 0.9701 | |
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| 0.0887 | 4.0 | 7192 | 0.1532 | 0.9631 | 0.8011 | 0.6295 | 0.7050 | 0.9708 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.0 |
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- Tokenizers 0.13.3 |
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