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distillbert-finetuned-finer-4-v3
ShadyML/distillbert-finetuned-finer-4-v3
distillbert-finetuned-finer-4-v3 is a token classification model from ShadyML. 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
- Mar 10, 2024
- Updated
- Mar 10, 2024
- SHA
- da85625b
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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. -->
distillbert-finetuned-finer-4-v3
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: 0.0223
- Precision: 0.9044
- Recall: 0.9318
- F1: 0.9179
- Accuracy: 0.9931
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 |
|---|---|---|---|---|---|---|---|
| 0.0248 | 1.0 | 2095 | 0.0271 | 0.8736 | 0.9052 | 0.8891 | 0.9907 |
| 0.0183 | 2.0 | 4190 | 0.0236 | 0.8864 | 0.9324 | 0.9088 | 0.9922 |
| 0.0118 | 3.0 | 6285 | 0.0223 | 0.9044 | 0.9318 | 0.9179 | 0.9931 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Mar 10, 2024
- Updated
- Mar 10, 2024