Training complete

README.md

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+---
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- accuracy
+model-index:
+- name: bert-finetuned-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. -->
+
+# bert-finetuned-ner
+
+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: 0.1793
+- Precision: 0.7556
+- Recall: 0.8015
+- Overall F1: 0.7779
+- Accuracy: 0.9669
+
+## 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 | Overall F1 | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:----------:|:--------:|
+| 0.0221        | 1.0   | 1041 | 0.1840          | 0.7401    | 0.7976 | 0.7678     | 0.9662   |
+| 0.0362        | 2.0   | 2082 | 0.1571          | 0.7490    | 0.8028 | 0.7750     | 0.9662   |
+| 0.0187        | 3.0   | 3123 | 0.1793          | 0.7556    | 0.8015 | 0.7779     | 0.9669   |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1