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B001_cleaned
Theoreticallyhugo/B001_cleaned
B001_cleaned is a text classification model from Theoreticallyhugo. 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
- Feb 10, 2024
- Updated
- Feb 10, 2024
- SHA
- 107c0020
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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. -->
B001_cleaned
This model is a fine-tuned version of distilbert-base-uncased on the essay_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 2.2117
- Accuracy: {'accuracy': 0.10526315789473684}
- Precision: {'precision': 0.013157894736842105}
- Recall: {'recall': 0.125}
- F1: {'f1': 0.02380952380952381}
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 13 | 2.2061 | {'accuracy': 0.10526315789473684} | {'precision': 0.013157894736842105} | {'recall': 0.125} | {'f1': 0.02380952380952381} |
| No log | 2.0 | 26 | 2.2050 | {'accuracy': 0.10526315789473684} | {'precision': 0.013157894736842105} | {'recall': 0.125} | {'f1': 0.02380952380952381} |
| No log | 3.0 | 39 | 2.2045 | {'accuracy': 0.10526315789473684} | {'precision': 0.013157894736842105} | {'recall': 0.125} | {'f1': 0.02380952380952381} |
| No log | 4.0 | 52 | 2.2117 | {'accuracy': 0.10526315789473684} | {'precision': 0.013157894736842105} | {'recall': 0.125} | {'f1': 0.02380952380952381} |
Framework versions
- Transformers 4.37.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Feb 10, 2024
- Updated
- Feb 10, 2024