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Heritage-in-the-Digital-Age
tgieruc/Heritage-in-the-Digital-Age
Heritage-in-the-Digital-Age is a text classification model from tgieruc. 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 27, 2022
- Updated
- Dec 27, 2022
- SHA
- 51e39fd3
Try a prompt
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-cola
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1797
- Matthews Correlation: 0.8587
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: 6.627434667917962e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 32
- 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 | Matthews Correlation |
|---|---|---|---|---|
| No log | 1.0 | 183 | 0.4053 | 0.6878 |
| No log | 2.0 | 366 | 0.3494 | 0.7153 |
| 0.4051 | 3.0 | 549 | 0.2312 | 0.8267 |
| 0.4051 | 4.0 | 732 | 0.1797 | 0.8587 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Dec 27, 2022
- Updated
- Dec 27, 2022