my_ner_model
This model is a fine-tuned version of DeepPavlov/rubert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5618
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.8411
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 |
---|---|---|---|---|---|---|---|
No log | 1.0 | 2 | 0.7150 | 0.0 | 0.0 | 0.0 | 0.8224 |
No log | 2.0 | 4 | 0.5618 | 0.0 | 0.0 | 0.0 | 0.8411 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.4.0+cu124
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for Romblebee/my_ner_model
Base model
DeepPavlov/rubert-base-cased