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--- |
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license: apache-2.0 |
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language: |
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- en |
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model-index: |
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- name: rttl-ai/SentyBert |
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results: |
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- task: |
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type: task-classification |
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name: Text Classification |
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dataset: |
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type: sst2 |
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name: sst2 |
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config: default |
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split: validation |
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metrics: |
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- type: f1 |
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value: 0.9992 |
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name: F1 Macro |
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- type: accuracy |
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value: 0.9992 |
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name: Accuracy |
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datasets: |
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- sst2 |
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- sst |
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--- |
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# rttl-ai/SentyBert |
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## Model Details |
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**Model Description:** This model is a fine-tune checkpoint of [bert-large-uncased](https://huggingface.co/bert-large-uncased), fine-tuned on SST-2. |
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This model reaches an accuracy of 99.92 on the dev set. |
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- **Developed by:** rttl-ai |
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- **Model Type:** Text Classification |
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- **Language(s):** English |
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- **License:** Apache-2.0 |
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- **Resources for more information:** |
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- The model was pre-trained with task-adaptive pre-training [TAPT](https://arxiv.org/pdf/2004.10964.pdf) with an increased masking rate, no corruption strategy, and using WWM, following [this paper](https://aclanthology.org/2023.eacl-main.217.pdf) |
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- fine-tuned on sst with subtrees |
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- fine-tuned on sst2 |
