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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_seed36_1311 |
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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_seed36_1311 |
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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: 0.4419 |
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- Precisions: 0.8943 |
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- Recall: 0.8153 |
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- F-measure: 0.8493 |
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- Accuracy: 0.9385 |
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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: 36 |
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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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| 0.4359 | 1.0 | 236 | 0.3021 | 0.8474 | 0.6948 | 0.7163 | 0.9077 | |
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| 0.2293 | 2.0 | 472 | 0.2484 | 0.8612 | 0.7522 | 0.7842 | 0.9258 | |
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| 0.1373 | 3.0 | 708 | 0.3033 | 0.7969 | 0.7892 | 0.7776 | 0.9250 | |
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| 0.0881 | 4.0 | 944 | 0.3218 | 0.8153 | 0.8103 | 0.8094 | 0.9299 | |
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| 0.0612 | 5.0 | 1180 | 0.3208 | 0.8357 | 0.8151 | 0.8225 | 0.9315 | |
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| 0.0378 | 6.0 | 1416 | 0.3553 | 0.8919 | 0.8173 | 0.8493 | 0.9405 | |
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| 0.0283 | 7.0 | 1652 | 0.4053 | 0.8575 | 0.8070 | 0.8270 | 0.9364 | |
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| 0.0229 | 8.0 | 1888 | 0.3789 | 0.8639 | 0.8236 | 0.8398 | 0.9354 | |
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| 0.0149 | 9.0 | 2124 | 0.4101 | 0.8856 | 0.8070 | 0.8387 | 0.9376 | |
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| 0.0073 | 10.0 | 2360 | 0.4419 | 0.8943 | 0.8153 | 0.8493 | 0.9385 | |
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| 0.0036 | 11.0 | 2596 | 0.4621 | 0.8882 | 0.8045 | 0.8392 | 0.9371 | |
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| 0.0045 | 12.0 | 2832 | 0.4494 | 0.8913 | 0.8093 | 0.8440 | 0.9383 | |
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| 0.0034 | 13.0 | 3068 | 0.4420 | 0.8795 | 0.8152 | 0.8422 | 0.9395 | |
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| 0.0014 | 14.0 | 3304 | 0.4494 | 0.8838 | 0.8100 | 0.8404 | 0.9390 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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