Blaine-Mason
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add model
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- README.md +8 -8
- pytorch_model.bin +1 -1
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README.md
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metric:
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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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This model is a fine-tuned version of [Blaine-Mason/hackMIT-finetuned-sst2](https://huggingface.co/Blaine-Mason/hackMIT-finetuned-sst2) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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- Accuracy: 0.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size:
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- eval_batch_size:
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- seed:
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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: 1
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.
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### Framework versions
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metric:
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name: Accuracy
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type: accuracy
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value: 0.8027522935779816
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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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This model is a fine-tuned version of [Blaine-Mason/hackMIT-finetuned-sst2](https://huggingface.co/Blaine-Mason/hackMIT-finetuned-sst2) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1086
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- Accuracy: 0.8028
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2.033238621168611e-06
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 30
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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: 1
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.0674 | 1.0 | 4210 | 1.1086 | 0.8028 |
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### Framework versions
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pytorch_model.bin
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