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update model card README.md
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README.md
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---
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license: mit
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base_model: prajjwal1/bert-tiny
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tags:
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- generated_from_trainer
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datasets:
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metrics:
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- accuracy
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model-index:
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name: Text Classification
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type: text-classification
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dataset:
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name:
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type:
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split: train
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args: '-904912027'
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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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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# 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
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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### Framework versions
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- Transformers 4.
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- Pytorch
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- Datasets 2.
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- Tokenizers 0.
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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: 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: 0.7833333333333333
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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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# 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: 0.5666
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- Accuracy: 0.7833
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.524 | 1.0 | 1500 | 0.4828 | 0.7617 |
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| 0.3834 | 2.0 | 3000 | 0.5569 | 0.7817 |
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| 0.3383 | 3.0 | 4500 | 0.5666 | 0.7833 |
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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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