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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: sentiment_bert |
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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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# sentiment_bert |
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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: 0.7469 |
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- Accuracy: 0.6802 |
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- F1: 0.6332 |
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- Precision: 0.6152 |
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- Recall: 0.6942 |
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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: 64 |
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- eval_batch_size: 64 |
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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: linear |
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- num_epochs: 5 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.7975 | 1.0 | 94 | 0.9153 | 0.4158 | 0.4603 | 0.5512 | 0.5862 | |
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| 0.7765 | 2.0 | 188 | 0.8220 | 0.6583 | 0.6023 | 0.5894 | 0.6461 | |
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| 0.71 | 3.0 | 282 | 0.8345 | 0.6062 | 0.5908 | 0.5955 | 0.6858 | |
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| 0.6439 | 4.0 | 376 | 0.7753 | 0.6568 | 0.6241 | 0.6133 | 0.7010 | |
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| 0.6623 | 5.0 | 470 | 0.7469 | 0.6802 | 0.6332 | 0.6152 | 0.6942 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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