End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google-bert/bert-large-cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-large-cased-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-cased-finetuned-ner-geocorpus
+
+This model is a fine-tuned version of [google-bert/bert-large-cased](https://huggingface.co/google-bert/bert-large-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1330
+- Precision: 0.868
+- Recall: 0.8872
+- F1: 0.8775
+- Accuracy: 0.9793
+
+## 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: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 16
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 0.9991 | 275  | 0.1429          | 0.7212    | 0.7318 | 0.7265 | 0.9613   |
+| 0.21          | 1.9982 | 550  | 0.1111          | 0.7211    | 0.8267 | 0.7703 | 0.9654   |
+| 0.21          | 2.9973 | 825  | 0.0979          | 0.8168    | 0.8168 | 0.8168 | 0.9725   |
+| 0.0651        | 4.0    | 1101 | 0.1088          | 0.7574    | 0.9011 | 0.8230 | 0.9678   |
+| 0.0651        | 4.9991 | 1376 | 0.1033          | 0.825     | 0.8904 | 0.8565 | 0.9744   |
+| 0.0305        | 5.9982 | 1651 | 0.1132          | 0.8908    | 0.8536 | 0.8718 | 0.9785   |
+| 0.0305        | 6.9973 | 1926 | 0.1127          | 0.8591    | 0.8823 | 0.8705 | 0.9786   |
+| 0.0153        | 8.0    | 2202 | 0.1155          | 0.8687    | 0.8814 | 0.8750 | 0.9795   |
+| 0.0153        | 8.9991 | 2477 | 0.1280          | 0.8860    | 0.8774 | 0.8817 | 0.9804   |
+| 0.0089        | 9.9909 | 2750 | 0.1330          | 0.868     | 0.8872 | 0.8775 | 0.9793   |
+
+
+### Framework versions
+
+- Transformers 4.46.2
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3

runs/Dec04_17-42-48_63b2597b7416/events.out.tfevents.1733334186.63b2597b7416.1245.0

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runs/Dec04_17-42-48_63b2597b7416/events.out.tfevents.1733338048.63b2597b7416.1245.1

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