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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: output |
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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 Emotion Detection |
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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: 0.2551 |
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- Precision: 0.9362 |
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- Recall: 0.9360 |
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- Fscore: 0.9359 |
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- Accuracy: 0.9360 |
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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 | Fscore | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 348 | 0.3054 | 0.9166 | 0.9144 | 0.9136 | 0.9144 | |
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| 0.5158 | 2.0 | 696 | 0.2551 | 0.9362 | 0.9360 | 0.9359 | 0.9360 | |
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| 0.1469 | 3.0 | 1044 | 0.3670 | 0.9283 | 0.9259 | 0.9245 | 0.9259 | |
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| 0.1469 | 4.0 | 1392 | 0.3833 | 0.9331 | 0.9317 | 0.9307 | 0.9317 | |
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| 0.0453 | 5.0 | 1740 | 0.4241 | 0.9356 | 0.9345 | 0.9342 | 0.9345 | |
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| 0.0237 | 6.0 | 2088 | 0.3750 | 0.9441 | 0.9439 | 0.9437 | 0.9439 | |
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| 0.0237 | 7.0 | 2436 | 0.3986 | 0.9389 | 0.9388 | 0.9385 | 0.9388 | |
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| 0.009 | 8.0 | 2784 | 0.4100 | 0.9407 | 0.9403 | 0.9397 | 0.9403 | |
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| 0.0053 | 9.0 | 3132 | 0.4005 | 0.9403 | 0.9403 | 0.9401 | 0.9403 | |
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| 0.0053 | 10.0 | 3480 | 0.3986 | 0.9410 | 0.9410 | 0.9408 | 0.9410 | |
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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 |
