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ternary_persian_sentiment_analysis

Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Inference Endpoints
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: sentence-transformers/LaBSE
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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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+ model-index:
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+ - name: ternary_persian_sentiment_analysis
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+ results: []
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+ ---
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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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+
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+ # ternary_persian_sentiment_analysis
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+
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+ This model is a fine-tuned version of [sentence-transformers/LaBSE](https://huggingface.co/sentence-transformers/LaBSE) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4914
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+ - Accuracy: 0.8458
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+ - F1 Score: 0.8459
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|
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+ | 0.496 | 1.0 | 1394 | 0.4708 | 0.8192 | 0.8186 |
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+ | 0.4177 | 2.0 | 2788 | 0.4914 | 0.8458 | 0.8459 |
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+ | 0.3237 | 3.0 | 4182 | 0.5736 | 0.8354 | 0.8356 |
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+ | 0.2874 | 4.0 | 5576 | 0.7309 | 0.8216 | 0.8217 |
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+ | 0.2142 | 5.0 | 6970 | 0.9256 | 0.8184 | 0.8187 |
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+ | 0.1494 | 6.0 | 8364 | 1.0608 | 0.8200 | 0.8197 |
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+ | 0.1396 | 7.0 | 9758 | 1.0638 | 0.8257 | 0.8256 |
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+ | 0.0983 | 8.0 | 11152 | 1.2088 | 0.8200 | 0.8200 |
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+ | 0.0907 | 9.0 | 12546 | 1.3653 | 0.8079 | 0.8083 |
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+ | 0.0727 | 10.0 | 13940 | 1.3032 | 0.8305 | 0.8307 |
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+ | 0.0526 | 11.0 | 15334 | 1.4689 | 0.8184 | 0.8184 |
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+ | 0.0413 | 12.0 | 16728 | 1.4875 | 0.8224 | 0.8227 |
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+ | 0.0265 | 13.0 | 18122 | 1.6185 | 0.8241 | 0.8242 |
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+ | 0.0366 | 14.0 | 19516 | 1.7135 | 0.8168 | 0.8168 |
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+ | 0.0251 | 15.0 | 20910 | 1.6607 | 0.8249 | 0.8251 |
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+ | 0.0151 | 16.0 | 22304 | 1.7922 | 0.8111 | 0.8111 |
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+ | 0.0159 | 17.0 | 23698 | 1.7303 | 0.8200 | 0.8201 |
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+ | 0.0163 | 18.0 | 25092 | 1.7555 | 0.8232 | 0.8232 |
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+ | 0.0178 | 19.0 | 26486 | 1.7680 | 0.8232 | 0.8232 |
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+ | 0.0147 | 20.0 | 27880 | 1.7546 | 0.8216 | 0.8217 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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