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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- emotion |
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metrics: |
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- accuracy |
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model-index: |
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- name: bnb-sentiment-model-saagie |
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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: emotion |
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type: emotion |
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args: split |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.93 |
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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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# bnb-sentiment-model-saagie |
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This model is a fine-tuned version of [j-hartmann/emotion-english-distilroberta-base](https://huggingface.co/j-hartmann/emotion-english-distilroberta-base) on the emotion dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2269 |
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- Accuracy: 0.93 |
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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: 3 |
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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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| 0.3839 | 1.0 | 1500 | 0.2857 | 0.9333 | |
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| 0.1902 | 2.0 | 3000 | 0.2143 | 0.9417 | |
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| 0.1159 | 3.0 | 4500 | 0.2269 | 0.93 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.8.1 |
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- Datasets 2.12.0 |
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- Tokenizers 0.12.1 |
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