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initial-dq-model
lucafrost/initial-dq-model
initial-dq-model is a token classification model from lucafrost. 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
- Jan 8, 2023
- Updated
- Jan 8, 2023
- SHA
- e79a3b26
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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. -->
initial-dq-model
This model is a fine-tuned version of distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1677
- Precision: 0.7763
- Recall: 0.9380
- F1: 0.8495
- Accuracy: 0.9423
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.2251 | 1.0 | 1220 | 0.1768 | 0.7481 | 0.9264 | 0.8277 | 0.9378 |
| 0.186 | 2.0 | 2440 | 0.1677 | 0.7763 | 0.9380 | 0.8495 | 0.9423 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.10.2+cu113
- Datasets 2.8.0
- Tokenizers 0.13.2
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Jan 8, 2023
- Updated
- Jan 8, 2023