Training complete

README.md

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+---
+license: mit
+base_model: dslim/bert-base-NER
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-finetuned-ner-ontonotes5
+  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-ontonotes5
+
+This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1634
+- Precision: 0.8620
+- Recall: 0.8849
+- F1: 0.8733
+- Accuracy: 0.9758
+
+## 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0372        | 1.0   | 7491  | 0.1188          | 0.8392    | 0.8799 | 0.8591 | 0.9738   |
+| 0.04          | 2.0   | 14982 | 0.1182          | 0.8562    | 0.8824 | 0.8691 | 0.9754   |
+| 0.0164        | 3.0   | 22473 | 0.1380          | 0.8561    | 0.8835 | 0.8696 | 0.9752   |
+| 0.0117        | 4.0   | 29964 | 0.1531          | 0.8618    | 0.8833 | 0.8724 | 0.9758   |
+| 0.0054        | 5.0   | 37455 | 0.1634          | 0.8620    | 0.8849 | 0.8733 | 0.9758   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1