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distilbert-base-uncased-test2
oyvindgrutle/distilbert-base-uncased-test2
distilbert-base-uncased-test2 is a token classification model from oyvindgrutle. Use it when you need labels on individual words, such as names. 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
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Aug 18, 2022
- Updated
- Aug 18, 2022
- SHA
- e0332b17
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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. -->
distilbert-base-uncased-test2
This model is a fine-tuned version of distilbert-base-uncased on the wnut_17 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2937
- Precision: 0.5410
- Recall: 0.3976
- F1: 0.4583
- Accuracy: 0.9469
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 213 | 0.2700 | 0.5102 | 0.3698 | 0.4288 | 0.9447 |
| No log | 2.0 | 426 | 0.2827 | 0.5687 | 0.3874 | 0.4609 | 0.9469 |
| 0.0553 | 3.0 | 639 | 0.2937 | 0.5410 | 0.3976 | 0.4583 | 0.9469 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Aug 18, 2022
- Updated
- Aug 18, 2022