End of training

README.md

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+---
+library_name: transformers
+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-harem
+  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-harem
+
+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: 0.3109
+- Precision: 0.6895
+- Recall: 0.6442
+- F1: 0.6661
+- Accuracy: 0.9512
+
+## 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        | 0.9978 | 281  | 0.2896          | 0.5442    | 0.4772 | 0.5085 | 0.9238   |
+| 0.3496        | 1.9973 | 562  | 0.2340          | 0.6811    | 0.5295 | 0.5958 | 0.9412   |
+| 0.3496        | 2.9969 | 843  | 0.2240          | 0.5876    | 0.5599 | 0.5734 | 0.9409   |
+| 0.1372        | 3.9964 | 1124 | 0.2540          | 0.6910    | 0.6223 | 0.6548 | 0.9403   |
+| 0.1372        | 4.9960 | 1405 | 0.2598          | 0.6433    | 0.6358 | 0.6395 | 0.9439   |
+| 0.0648        | 5.9956 | 1686 | 0.2377          | 0.6945    | 0.6442 | 0.6684 | 0.9497   |
+| 0.0648        | 6.9951 | 1967 | 0.2822          | 0.6965    | 0.6425 | 0.6684 | 0.9501   |
+| 0.0316        | 7.9982 | 2249 | 0.2958          | 0.7044    | 0.6509 | 0.6766 | 0.9518   |
+| 0.0148        | 8.9978 | 2530 | 0.3006          | 0.6944    | 0.6476 | 0.6702 | 0.9496   |
+| 0.0148        | 9.9938 | 2810 | 0.3109          | 0.6895    | 0.6442 | 0.6661 | 0.9512   |
+
+
+### Framework versions
+
+- Transformers 4.46.2
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3

runs/Dec04_16-04-28_9db9fd54087a/events.out.tfevents.1733331288.9db9fd54087a.246.1

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