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--- |
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license: apache-2.0 |
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base_model: google-bert/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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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: nlp_1 |
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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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# nlp_1 |
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This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4215 |
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- Accuracy: 0.9037 |
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- Precision: 0.8944 |
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- Recall: 0.9025 |
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- F1: 0.8968 |
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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: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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: cosine |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.3252 | 1.0 | 48 | 0.4194 | 0.8670 | 0.8671 | 0.8619 | 0.8617 | |
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| 0.1803 | 2.0 | 96 | 0.3779 | 0.8853 | 0.8807 | 0.8788 | 0.8773 | |
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| 0.1713 | 3.0 | 144 | 0.4097 | 0.8945 | 0.8864 | 0.8924 | 0.8857 | |
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| 0.1359 | 4.0 | 192 | 0.4012 | 0.8945 | 0.8919 | 0.8841 | 0.8873 | |
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| 0.1201 | 5.0 | 240 | 0.3770 | 0.8899 | 0.8809 | 0.8876 | 0.8818 | |
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| 0.0735 | 6.0 | 288 | 0.4204 | 0.8991 | 0.8934 | 0.8975 | 0.8921 | |
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| 0.0807 | 7.0 | 336 | 0.4092 | 0.9083 | 0.9059 | 0.9020 | 0.9024 | |
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| 0.1066 | 8.0 | 384 | 0.4181 | 0.8991 | 0.8894 | 0.8928 | 0.8903 | |
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| 0.0615 | 9.0 | 432 | 0.4212 | 0.9083 | 0.8988 | 0.9066 | 0.9014 | |
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| 0.071 | 10.0 | 480 | 0.4215 | 0.9037 | 0.8944 | 0.9025 | 0.8968 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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