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distilbert-base-uncased-finetuned-sst2-pt
rwang5688/distilbert-base-uncased-finetuned-sst2-pt
distilbert-base-uncased-finetuned-sst2-pt is a text classification model from rwang5688. 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 10, 2023
- Updated
- Feb 23, 2024
- SHA
- 1106837b
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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-pt
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: 0.5249
- Accuracy: 0.9071
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 |
|---|---|---|---|---|
| 0.1906 | 1.0 | 4210 | 0.3109 | 0.8979 |
| 0.141 | 2.0 | 8420 | 0.4039 | 0.8922 |
| 0.0925 | 3.0 | 12630 | 0.3897 | 0.9002 |
| 0.0627 | 4.0 | 16840 | 0.4421 | 0.9048 |
| 0.0422 | 5.0 | 21050 | 0.5249 | 0.9071 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Apr 10, 2023
- Updated
- Feb 23, 2024