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---
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license: mit
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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: BiBert-MultiTask-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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# BiBert-MultiTask-1
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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: 1.2971
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- Accuracy: 0.7090
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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: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 345 | 1.2060 | 0.7063 |
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| 0.7739 | 2.0 | 690 | 1.1887 | 0.7103 |
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| 0.6183 | 3.0 | 1035 | 1.2281 | 0.7247 |
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| 0.6183 | 4.0 | 1380 | 1.2635 | 0.7103 |
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| 0.5103 | 5.0 | 1725 | 1.2971 | 0.7090 |
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### Framework versions
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- Transformers 4.22.2
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- Pytorch 1.12.1+cu113
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- Datasets 2.6.1
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- Tokenizers 0.12.1
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