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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: bert-base-multilingual-uncased
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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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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: bert_product_classifier_name
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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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+ # bert_product_classifier_name
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+
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+ This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3406
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+ - Accuracy: 0.9517
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+ - F1: 0.9513
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+ - Precision: 0.9514
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+ - Recall: 0.9517
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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: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.8574 | 1.0 | 960 | 0.3075 | 0.9079 | 0.9069 | 0.9077 | 0.9079 |
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+ | 0.267 | 2.0 | 1920 | 0.2432 | 0.9292 | 0.9294 | 0.9307 | 0.9292 |
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+ | 0.1596 | 3.0 | 2880 | 0.2228 | 0.9411 | 0.9408 | 0.9409 | 0.9411 |
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+ | 0.1094 | 4.0 | 3840 | 0.2540 | 0.9452 | 0.9447 | 0.9447 | 0.9452 |
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+ | 0.0755 | 5.0 | 4800 | 0.2652 | 0.9470 | 0.9471 | 0.9472 | 0.9470 |
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+ | 0.0506 | 6.0 | 5760 | 0.2924 | 0.9492 | 0.9491 | 0.9491 | 0.9492 |
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+ | 0.0364 | 7.0 | 6720 | 0.3251 | 0.9475 | 0.9470 | 0.9476 | 0.9475 |
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+ | 0.022 | 8.0 | 7680 | 0.3271 | 0.9518 | 0.9515 | 0.9514 | 0.9518 |
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+ | 0.0122 | 9.0 | 8640 | 0.3368 | 0.9522 | 0.9520 | 0.9519 | 0.9522 |
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+ | 0.0103 | 10.0 | 9600 | 0.3406 | 0.9517 | 0.9513 | 0.9514 | 0.9517 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.0
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3
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