Model save

README.md

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----
-license: mit
----
+---
+library_name: transformers
+license: cc-by-4.0
+base_model: NbAiLab/nb-bert-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: nb-bert-norne-ner
+  results: []
+---
+
+<!-- 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. -->
+
+# nb-bert-norne-ner
+
+This model is a fine-tuned version of [NbAiLab/nb-bert-base](https://huggingface.co/NbAiLab/nb-bert-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0430
+- Precision: 0.9277
+- Recall: 0.9296
+- F1: 0.9287
+- Accuracy: 0.9951
+
+## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0233        | 1.0   | 3734  | 0.0272          | 0.8978    | 0.9109 | 0.9043 | 0.9939   |
+| 0.0165        | 2.0   | 7468  | 0.0214          | 0.9200    | 0.9228 | 0.9214 | 0.9949   |
+| 0.0071        | 3.0   | 11202 | 0.0269          | 0.9218    | 0.9222 | 0.9220 | 0.9951   |
+| 0.0042        | 4.0   | 14936 | 0.0275          | 0.9237    | 0.9259 | 0.9248 | 0.9951   |
+| 0.0025        | 5.0   | 18670 | 0.0331          | 0.9226    | 0.9279 | 0.9253 | 0.9951   |
+| 0.0014        | 6.0   | 22404 | 0.0370          | 0.9204    | 0.9276 | 0.9240 | 0.9949   |
+| 0.0015        | 7.0   | 26138 | 0.0389          | 0.9225    | 0.9259 | 0.9242 | 0.9951   |
+| 0.0           | 8.0   | 29872 | 0.0404          | 0.9263    | 0.9310 | 0.9286 | 0.9953   |
+| 0.0003        | 9.0   | 33606 | 0.0426          | 0.9259    | 0.9300 | 0.9279 | 0.9952   |
+| 0.0           | 10.0  | 37340 | 0.0430          | 0.9277    | 0.9296 | 0.9287 | 0.9951   |
+
+
+### Framework versions
+
+- Transformers 4.57.3
+- Pytorch 2.9.1
+- Datasets 4.4.1
+- Tokenizers 0.22.1