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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: 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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+ - recall
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+ - accuracy
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+ model-index:
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+ - name: multibert_1210seed7
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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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+ # multibert_1210seed7
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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: 0.5019
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+ - Precisions: 0.8874
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+ - Recall: 0.7790
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+ - F-measure: 0.8105
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+ - Accuracy: 0.9107
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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: 7.5e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 7
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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: 14
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
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+ | 0.6032 | 1.0 | 236 | 0.4733 | 0.8608 | 0.6507 | 0.6853 | 0.8645 |
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+ | 0.3527 | 2.0 | 472 | 0.3790 | 0.8098 | 0.7259 | 0.7383 | 0.8826 |
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+ | 0.2198 | 3.0 | 708 | 0.4191 | 0.8209 | 0.7632 | 0.7816 | 0.8936 |
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+ | 0.1359 | 4.0 | 944 | 0.4433 | 0.8430 | 0.7344 | 0.7590 | 0.8924 |
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+ | 0.0862 | 5.0 | 1180 | 0.5207 | 0.8067 | 0.7697 | 0.7838 | 0.8947 |
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+ | 0.0637 | 6.0 | 1416 | 0.5019 | 0.8874 | 0.7790 | 0.8105 | 0.9107 |
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+ | 0.0454 | 7.0 | 1652 | 0.5048 | 0.8049 | 0.8135 | 0.8070 | 0.9058 |
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+ | 0.0318 | 8.0 | 1888 | 0.5969 | 0.8135 | 0.7710 | 0.7845 | 0.9003 |
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+ | 0.024 | 9.0 | 2124 | 0.6388 | 0.8295 | 0.7999 | 0.8057 | 0.9048 |
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+ | 0.0138 | 10.0 | 2360 | 0.6448 | 0.8304 | 0.7727 | 0.7949 | 0.9033 |
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+ | 0.0084 | 11.0 | 2596 | 0.6589 | 0.8216 | 0.7756 | 0.7936 | 0.9017 |
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+ | 0.0091 | 12.0 | 2832 | 0.6471 | 0.8340 | 0.7683 | 0.7952 | 0.9045 |
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+ | 0.005 | 13.0 | 3068 | 0.6817 | 0.8600 | 0.7662 | 0.8034 | 0.9073 |
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+ | 0.0045 | 14.0 | 3304 | 0.6774 | 0.8397 | 0.7680 | 0.7976 | 0.9077 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
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