Training complete

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: ner-model
+  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. -->
+
+# ner-model
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1297
+- Precision: 0.8229
+- Recall: 0.8866
+- F1: 0.8535
+- Accuracy: 0.9667
+
+## 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: 1e-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 |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1752        | 1.0   | 2489  | 0.1261          | 0.7649    | 0.8137 | 0.7885 | 0.9549   |
+| 0.1076        | 2.0   | 4978  | 0.1184          | 0.7881    | 0.8592 | 0.8221 | 0.9611   |
+| 0.074         | 3.0   | 7467  | 0.1137          | 0.7985    | 0.8802 | 0.8374 | 0.9634   |
+| 0.0634        | 4.0   | 9956  | 0.1239          | 0.8125    | 0.8927 | 0.8507 | 0.9651   |
+| 0.0387        | 5.0   | 12445 | 0.1297          | 0.8229    | 0.8866 | 0.8535 | 0.9667   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.0+cu121
+- Datasets 3.0.0
+- Tokenizers 0.19.1