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End of training

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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: google-bert/bert-base-multilingual-cased
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: m-bert
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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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+ # m-bert
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+
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+ This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3141
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+ - Precison: 0.8543
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+ - Recall: 0.8566
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+ - F1: 0.8554
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+ - Accuracy: 0.8594
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+ - Jaccard: 0.7848
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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: 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: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precison | Recall | F1 | Accuracy | Jaccard |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:--------:|:-------:|
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+ | 0.4088 | 1.0 | 1513 | 0.3141 | 0.8543 | 0.8566 | 0.8554 | 0.8594 | 0.7848 |
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+ | 0.3328 | 2.0 | 3026 | 0.3161 | 0.8685 | 0.8530 | 0.8587 | 0.8656 | 0.8018 |
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+ | 0.2521 | 3.0 | 4539 | 0.3444 | 0.8729 | 0.8700 | 0.8714 | 0.8758 | 0.8105 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.1
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+ - Pytorch 2.1.2
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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