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--- |
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base_model: HooshvareLab/bert-base-parsbert-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- accuracy |
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model-index: |
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- name: Persian-Text-Sentiment-Bert-V1 |
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results: [] |
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language: |
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- fa |
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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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# Persian-Text-Sentiment-Bert-V1 |
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This model is a fine-tuned version of [HooshvareLab/bert-base-parsbert-uncased](https://huggingface.co./HooshvareLab/bert-base-parsbert-uncased) on a custom dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3265 |
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- Precision: 0.8727 |
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- Recall: 0.8716 |
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- F1-score: 0.8715 |
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- Accuracy: 0.8716 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1-score | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:--------:|:--------:| |
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| 0.3097 | 1.0 | 3491 | 0.3265 | 0.8727 | 0.8716 | 0.8715 | 0.8716 | |
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| 0.2686 | 2.0 | 6982 | 0.3602 | 0.8785 | 0.8758 | 0.8756 | 0.8758 | |
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| 0.2137 | 3.0 | 10473 | 0.3828 | 0.8759 | 0.8724 | 0.8721 | 0.8724 | |
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| 0.1823 | 4.0 | 13964 | 0.5545 | 0.8637 | 0.8636 | 0.8636 | 0.8636 | |
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| 0.1346 | 5.0 | 17455 | 0.6295 | 0.8572 | 0.8566 | 0.8566 | 0.8566 | |
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| 0.1001 | 6.0 | 20946 | 0.8501 | 0.8606 | 0.8604 | 0.8604 | 0.8604 | |
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| 0.071 | 7.0 | 24437 | 1.0192 | 0.8596 | 0.8594 | 0.8594 | 0.8594 | |
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| 0.0604 | 8.0 | 27928 | 1.0449 | 0.8553 | 0.8553 | 0.8553 | 0.8553 | |
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| 0.0312 | 9.0 | 31419 | 1.1677 | 0.8598 | 0.8598 | 0.8598 | 0.8598 | |
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| 0.022 | 10.0 | 34910 | 1.2128 | 0.8593 | 0.8591 | 0.8591 | 0.8591 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
