End of training

README.md

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+---
+license: apache-2.0
+base_model: google/rembert
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: rembert-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. -->
+
+# rembert-finetuned-ner
+
+This model is a fine-tuned version of [google/rembert](https://huggingface.co/google/rembert) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1419
+- Precision: 0.9136
+- Recall: 0.9285
+- F1: 0.9210
+- Accuracy: 0.9811
+
+## 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 | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0644        | 1.0   | 1756 | 0.0819          | 0.9075    | 0.9154 | 0.9114 | 0.9837   |
+| 0.0261        | 2.0   | 3512 | 0.0440          | 0.9576    | 0.9605 | 0.9590 | 0.9906   |
+| 0.0121        | 3.0   | 5268 | 0.0415          | 0.9622    | 0.9682 | 0.9652 | 0.9917   |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.0
+- Tokenizers 0.15.0

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