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results
sumups-ai/results
results is a token classification model from sumups-ai. 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
- bert
- Access
- Public
- Created
- Dec 12, 2022
- Updated
- Dec 13, 2022
- SHA
- 30f885ba
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. -->
results
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4578
- Precision: 0.0060
- Recall: 0.0286
- F1: 0.0099
- Accuracy: 0.4288
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 8 | 1.6449 | 0.0 | 0.0 | 0.0 | 0.3860 |
| No log | 2.0 | 16 | 1.5439 | 0.0014 | 0.0071 | 0.0023 | 0.4025 |
| No log | 3.0 | 24 | 1.4986 | 0.0068 | 0.0286 | 0.0110 | 0.4176 |
| No log | 4.0 | 32 | 1.4603 | 0.0033 | 0.0143 | 0.0054 | 0.4285 |
| No log | 5.0 | 40 | 1.4578 | 0.0060 | 0.0286 | 0.0099 | 0.4288 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Dec 12, 2022
- Updated
- Dec 13, 2022