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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_1210seed24 |
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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_1210seed24 |
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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: 0.6397 |
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- Precisions: 0.8875 |
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- Recall: 0.7915 |
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- F-measure: 0.8255 |
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- Accuracy: 0.9112 |
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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: 24 |
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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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| 0.5949 | 1.0 | 236 | 0.4396 | 0.8425 | 0.6484 | 0.6768 | 0.8569 | |
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| 0.3352 | 2.0 | 472 | 0.4132 | 0.7836 | 0.7344 | 0.7453 | 0.8862 | |
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| 0.2148 | 3.0 | 708 | 0.3528 | 0.8396 | 0.7759 | 0.8020 | 0.8985 | |
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| 0.1389 | 4.0 | 944 | 0.4093 | 0.8386 | 0.7431 | 0.7775 | 0.8931 | |
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| 0.099 | 5.0 | 1180 | 0.4169 | 0.8501 | 0.7998 | 0.8200 | 0.9022 | |
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| 0.078 | 6.0 | 1416 | 0.4629 | 0.7912 | 0.7756 | 0.7815 | 0.8900 | |
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| 0.0536 | 7.0 | 1652 | 0.4658 | 0.8394 | 0.8096 | 0.8235 | 0.9098 | |
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| 0.0316 | 8.0 | 1888 | 0.5609 | 0.8440 | 0.7790 | 0.8044 | 0.9019 | |
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| 0.0217 | 9.0 | 2124 | 0.5870 | 0.8686 | 0.7814 | 0.8128 | 0.9055 | |
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| 0.0126 | 10.0 | 2360 | 0.5636 | 0.8613 | 0.7997 | 0.8255 | 0.9059 | |
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| 0.0115 | 11.0 | 2596 | 0.5978 | 0.8721 | 0.7964 | 0.8232 | 0.9093 | |
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| 0.0082 | 12.0 | 2832 | 0.6072 | 0.8645 | 0.7904 | 0.8184 | 0.9098 | |
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| 0.0042 | 13.0 | 3068 | 0.6332 | 0.8801 | 0.7903 | 0.8230 | 0.9104 | |
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| 0.0033 | 14.0 | 3304 | 0.6397 | 0.8875 | 0.7915 | 0.8255 | 0.9112 | |
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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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