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
+- wer
+model-index:
+- name: bert-finetuned-ner-tokenizer
+  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-tokenizer
+
+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: 0.0280
+- Precision: 0.7896
+- Recall: 0.8536
+- F1: 0.8203
+- Accuracy: 0.9919
+- Wer: 0.0079
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:------:|
+| 0.0515        | 1.0   | 768  | 0.0273          | 0.7510    | 0.8495 | 0.7972 | 0.9907   | 0.0089 |
+| 0.0192        | 2.0   | 1536 | 0.0259          | 0.7567    | 0.8627 | 0.8062 | 0.9911   | 0.0086 |
+| 0.0158        | 3.0   | 2304 | 0.0259          | 0.7828    | 0.8565 | 0.8180 | 0.9916   | 0.0082 |
+| 0.0111        | 4.0   | 3072 | 0.0280          | 0.7896    | 0.8536 | 0.8203 | 0.9919   | 0.0079 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1