End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: distilbert-base-uncased-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. -->
+
+# distilbert-base-uncased-finetuned-ner
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: nan
+- Precision: 0.9222
+- Recall: 0.9253
+- F1: 0.9237
+- 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: 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.262         | 1.0   | 878  | nan             | 0.8873    | 0.9168 | 0.9018 | 0.9778   |
+| 0.0607        | 2.0   | 1756 | nan             | 0.9156    | 0.9192 | 0.9174 | 0.9807   |
+| 0.0433        | 3.0   | 2634 | nan             | 0.9203    | 0.9262 | 0.9232 | 0.9814   |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.2.0
+- Datasets 2.17.0
+- Tokenizers 0.15.2

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