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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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<!-- 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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# multibert_1210seed7 |
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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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## 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: 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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### Training results |
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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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### Framework versions |
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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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