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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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datasets: |
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- sst2 |
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metrics: |
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- accuracy |
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model-index: |
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- name: 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: sst2 |
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type: sst2 |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7816666666666666 |
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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-model-saagie |
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This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on the sst2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5403 |
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- Accuracy: 0.7817 |
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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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| 0.523 | 1.0 | 1500 | 0.4783 | 0.7667 | |
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| 0.3858 | 2.0 | 3000 | 0.5265 | 0.7867 | |
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| 0.3384 | 3.0 | 4500 | 0.5403 | 0.7817 | |
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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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