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my-text-classification-finetuned-v1
cwchang/my-text-classification-finetuned-v1
my-text-classification-finetuned-v1 is a text classification model from cwchang. 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
- Dec 1, 2023
- Updated
- Dec 1, 2023
- SHA
- 2a06295e
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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. -->
my-text-classification-finetuned-v1
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: 0.3949
- Accuracy: 0.943
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: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|---|
| No log | 1.0 | 469 | 2.7586 | 0.8023 |
| 3.9476 | 2.0 | 938 | 1.2001 | 0.898 |
| 1.8343 | 3.0 | 1407 | 0.6269 | 0.928 |
| 0.8038 | 4.0 | 1876 | 0.4387 | 0.9403 |
| 0.4445 | 5.0 | 2345 | 0.3949 | 0.943 |
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
- Dec 1, 2023
- Updated
- Dec 1, 2023