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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- nyu-mll/glue |
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metrics: |
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- accuracy |
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model_index: |
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- name: bert-base-uncased-finetuned-sst2 |
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results: |
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- dataset: |
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name: glue |
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type: glue |
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args: sst2 |
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metric: |
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name: Accuracy |
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type: accuracy |
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value: 0.926605504587156 |
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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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# bert-base-uncased-finetuned-sst2 |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2716 |
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- Accuracy: 0.9266 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 5 |
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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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| 0.1666 | 1.0 | 2105 | 0.2403 | 0.9232 | |
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| 0.1122 | 2.0 | 4210 | 0.2716 | 0.9266 | |
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| 0.0852 | 3.0 | 6315 | 0.3150 | 0.9232 | |
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| 0.056 | 4.0 | 8420 | 0.3209 | 0.9163 | |
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| 0.0344 | 5.0 | 10525 | 0.3740 | 0.9243 | |
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### Framework versions |
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- Transformers 4.9.2 |
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- Pytorch 1.8.1 |
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- Datasets 1.11.0 |
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- Tokenizers 0.10.1 |
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