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distilbert-base-uncased-finetuned-glue_sst2
markuscolab/distilbert-base-uncased-finetuned-glue_sst2
distilbert-base-uncased-finetuned-glue_sst2 is a text classification model from markuscolab. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Nov 17, 2023
- Updated
- Nov 18, 2023
- SHA
- e32ac534
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Base models
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. -->
distilbert-base-uncased-finetuned-glue_sst2
This model is a fine-tuned version of distilbert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.4097
- Accuracy: 0.9060
- F1: 0.9059
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.1853 | 1.0 | 4210 | 0.2735 | 0.9117 | 0.9116 |
| 0.1299 | 2.0 | 8420 | 0.3569 | 0.9083 | 0.9082 |
| 0.0957 | 3.0 | 12630 | 0.4097 | 0.9060 | 0.9059 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Nov 17, 2023
- Updated
- Nov 18, 2023