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hackMIT-finetuned-sst2
Blaine-Mason/hackMIT-finetuned-sst2
hackMIT-finetuned-sst2 is a text classification model from Blaine-Mason. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Aug 25, 2021
- SHA
- 9aeeeb2b
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Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
hackMIT-finetuned-sst2
This model is a fine-tuned version of Blaine-Mason/hackMIT-finetuned-sst2 on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 1.1086
- Accuracy: 0.8028
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2.033238621168611e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 30
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0674 | 1.0 | 4210 | 1.1086 | 0.8028 |
Framework versions
- Transformers 4.9.2
- Pytorch 1.9.0+cu102
- Datasets 1.11.0
- Tokenizers 0.10.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Mar 2, 2022
- Updated
- Aug 25, 2021