Training complete

README.md

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+---
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-ner-2
+  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. -->
+
+# bert-ner-2
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7358
+- Precision: 0.1646
+- Recall: 0.4605
+- F1: 0.2425
+- Accuracy: 0.8784
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 149  | 0.5651          | 0.1347    | 0.4192 | 0.2038 | 0.8686   |
+| No log        | 2.0   | 298  | 0.5818          | 0.1440    | 0.4227 | 0.2148 | 0.8785   |
+| No log        | 3.0   | 447  | 0.6011          | 0.1432    | 0.3986 | 0.2107 | 0.8808   |
+| 0.0328        | 4.0   | 596  | 0.5546          | 0.1613    | 0.3986 | 0.2297 | 0.8955   |
+| 0.0328        | 5.0   | 745  | 0.7685          | 0.1371    | 0.4467 | 0.2098 | 0.8600   |
+| 0.0328        | 6.0   | 894  | 0.7755          | 0.1486    | 0.4570 | 0.2243 | 0.8686   |
+| 0.0102        | 7.0   | 1043 | 0.6831          | 0.1669    | 0.4570 | 0.2445 | 0.8834   |
+| 0.0102        | 8.0   | 1192 | 0.7698          | 0.1524    | 0.4639 | 0.2294 | 0.8715   |
+| 0.0102        | 9.0   | 1341 | 0.7303          | 0.1681    | 0.4708 | 0.2477 | 0.8791   |
+| 0.0102        | 10.0  | 1490 | 0.7358          | 0.1646    | 0.4605 | 0.2425 | 0.8784   |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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