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--- |
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license: apache-2.0 |
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base_model: dadashzadeh/tiny-bert-Sentiment-persian |
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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: tiny-bert-Sentiment-persian |
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results: [] |
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datasets: |
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- hezarai/sentiment-dksf |
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language: |
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- fa |
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pipeline_tag: text-classification |
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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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# tiny-bert-Sentiment-persian |
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This model is a fine-tuned version of [dadashzadeh/tiny-bert-Sentiment-persian](https://huggingface.co/dadashzadeh/tiny-bert-Sentiment-persian) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6553 |
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- Accuracy: 0.7611 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 45 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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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: 12 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:-----:|:---------------:|:--------:| |
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| 0.6157 | 0.9999 | 3575 | 0.6703 | 0.7577 | |
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| 0.5833 | 1.9999 | 7150 | 0.7599 | 0.7171 | |
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| 0.6015 | 2.9998 | 10725 | 0.6824 | 0.7590 | |
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| 0.5601 | 4.0 | 14301 | 0.6780 | 0.7533 | |
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| 0.5699 | 4.9999 | 17876 | 0.7071 | 0.7356 | |
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| 0.5519 | 5.9999 | 21451 | 0.6931 | 0.7391 | |
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| 0.5436 | 6.9998 | 25026 | 0.6736 | 0.7629 | |
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| 0.5482 | 8.0 | 28602 | 0.6567 | 0.7685 | |
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| 0.5367 | 8.9999 | 32177 | 0.6553 | 0.7611 | |
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| 0.5399 | 9.9999 | 35752 | 0.6691 | 0.7616 | |
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| 0.5112 | 10.9998 | 39327 | 0.6785 | 0.7564 | |
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| 0.5113 | 11.9992 | 42900 | 0.6773 | 0.7572 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.2+cu118 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
