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--- |
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license: mit |
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base_model: nlptown/bert-base-multilingual-uncased-sentiment |
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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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model-index: |
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- name: test_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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# test_bert |
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This model is a fine-tuned version of [nlptown/bert-base-multilingual-uncased-sentiment](https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8332 |
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- Accuracy: 0.6817 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.1121 | 0.13 | 500 | 0.9841 | 0.6302 | |
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| 1.0067 | 0.25 | 1000 | 0.9490 | 0.6499 | |
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| 0.9325 | 0.38 | 1500 | 0.9200 | 0.6577 | |
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| 0.9301 | 0.51 | 2000 | 0.9684 | 0.6418 | |
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| 0.927 | 0.63 | 2500 | 0.9837 | 0.6234 | |
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| 0.9067 | 0.76 | 3000 | 0.8973 | 0.6572 | |
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| 0.8986 | 0.88 | 3500 | 0.8663 | 0.6747 | |
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| 0.8964 | 1.01 | 4000 | 0.8408 | 0.6767 | |
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| 0.8115 | 1.14 | 4500 | 0.8478 | 0.6696 | |
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| 0.8081 | 1.26 | 5000 | 0.8600 | 0.6681 | |
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| 0.7896 | 1.39 | 5500 | 0.8569 | 0.6747 | |
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| 0.8075 | 1.52 | 6000 | 0.8353 | 0.6767 | |
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| 0.802 | 1.64 | 6500 | 0.8261 | 0.6767 | |
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| 0.768 | 1.77 | 7000 | 0.8289 | 0.6782 | |
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| 0.7505 | 1.9 | 7500 | 0.8332 | 0.6817 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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