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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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datasets: |
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- amazon_reviews_multi |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: amazon-reviews-finetuning-bert-base-sentiment |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: amazon_reviews_multi |
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type: amazon_reviews_multi |
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config: en |
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split: validation |
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args: en |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.5764 |
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- name: F1 |
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type: f1 |
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value: 0.5738591890717804 |
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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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# amazon-reviews-finetuning-bert-base-sentiment |
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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 amazon_reviews_multi dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0136 |
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- Accuracy: 0.5764 |
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- F1: 0.5739 |
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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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- 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 | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.9867 | 1.0 | 1563 | 0.9814 | 0.5792 | 0.5677 | |
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| 0.8435 | 2.0 | 3126 | 1.0136 | 0.5764 | 0.5739 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.14.6.dev0 |
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- Tokenizers 0.13.3 |
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