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distilbert-base-uncased-finetuned-sst2
kkater/distilbert-base-uncased-finetuned-sst2
distilbert-base-uncased-finetuned-sst2 is a text classification model from kkater. 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
- Apr 29, 2024
- Updated
- Apr 29, 2024
- SHA
- 747b6048
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Base models
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-sst2
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5504
- Accuracy: 0.9060
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
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1843 | 1.0 | 4210 | 0.2870 | 0.9025 |
| 0.1391 | 2.0 | 8420 | 0.4051 | 0.8979 |
| 0.0941 | 3.0 | 12630 | 0.3839 | 0.9002 |
| 0.0641 | 4.0 | 16840 | 0.4454 | 0.9037 |
| 0.0403 | 5.0 | 21050 | 0.5504 | 0.9060 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Apr 29, 2024
- Updated
- Apr 29, 2024