End of training

README.md

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+---
+license: apache-2.0
+base_model: google-bert/bert-large-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-large-uncased-finetuned-ner-geocorpus
+  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-large-uncased-finetuned-ner-geocorpus
+
+This model is a fine-tuned version of [google-bert/bert-large-uncased](https://huggingface.co/google-bert/bert-large-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1293
+- Precision: 0.8171
+- Recall: 0.8806
+- F1: 0.8476
+- Accuracy: 0.9721
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 0.9955 | 137  | 0.2292          | 0.4527    | 0.3450 | 0.3916 | 0.9378   |
+| No log        | 1.9982 | 275  | 0.1339          | 0.6814    | 0.7175 | 0.6990 | 0.9606   |
+| No log        | 2.9936 | 412  | 0.1147          | 0.7385    | 0.8057 | 0.7706 | 0.9647   |
+| 0.2052        | 3.9964 | 550  | 0.1217          | 0.7099    | 0.8607 | 0.7781 | 0.9611   |
+| 0.2052        | 4.9991 | 688  | 0.1076          | 0.7705    | 0.8531 | 0.8097 | 0.9674   |
+| 0.2052        | 5.9946 | 825  | 0.1130          | 0.7970    | 0.8483 | 0.8219 | 0.9701   |
+| 0.2052        | 6.9973 | 963  | 0.1332          | 0.7357    | 0.8758 | 0.7997 | 0.9637   |
+| 0.0384        | 8.0    | 1101 | 0.1241          | 0.7798    | 0.8929 | 0.8325 | 0.9690   |
+| 0.0384        | 8.9955 | 1238 | 0.1241          | 0.8303    | 0.8720 | 0.8507 | 0.9728   |
+| 0.0384        | 9.9546 | 1370 | 0.1293          | 0.8171    | 0.8806 | 0.8476 | 0.9721   |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.1.2
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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