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rubert-base-cased-conversational_ner-v1
Data-Lab/rubert-base-cased-conversational_ner-v1
rubert-base-cased-conversational_ner-v1 is a token classification model from Data-Lab. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Sep 18, 2023
- Updated
- Oct 26, 2023
- SHA
- 2b665935
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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. -->
rubert-base-cased-conversational_ner-v2
This model is a fine-tuned version of DeepPavlov/rubert-base-cased-conversational on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1360
- Precision: 0.7324
- Recall: 0.7939
- F1: 0.7619
- Accuracy: 0.9289
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 60 | 0.2248 | 0.5069 | 0.5573 | 0.5309 | 0.8591 |
| No log | 2.0 | 120 | 0.1435 | 0.6966 | 0.7710 | 0.7319 | 0.9289 |
| No log | 3.0 | 180 | 0.1360 | 0.7324 | 0.7939 | 0.7619 | 0.9289 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- Created
- Sep 18, 2023
- Updated
- Oct 26, 2023