End of training

README.md

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+---
+license: apache-2.0
+base_model: google-bert/bert-base-multilingual-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-base-multilingual-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-base-multilingual-uncased-finetuned-ner-harem
+
+This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1203
+- Precision: 0.7859
+- Recall: 0.8221
+- F1: 0.8036
+- Accuracy: 0.9743
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- 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        | 1.0   | 141  | 0.1591          | 0.6755    | 0.6258 | 0.6497 | 0.9589   |
+| No log        | 2.0   | 282  | 0.1048          | 0.7171    | 0.7699 | 0.7426 | 0.9700   |
+| No log        | 3.0   | 423  | 0.1036          | 0.7407    | 0.7975 | 0.7681 | 0.9692   |
+| 0.1273        | 4.0   | 564  | 0.1028          | 0.7713    | 0.8067 | 0.7886 | 0.9724   |
+| 0.1273        | 5.0   | 705  | 0.1029          | 0.8102    | 0.8252 | 0.8176 | 0.9743   |
+| 0.1273        | 6.0   | 846  | 0.1067          | 0.7635    | 0.8221 | 0.7917 | 0.9731   |
+| 0.1273        | 7.0   | 987  | 0.1140          | 0.7794    | 0.8344 | 0.8059 | 0.9729   |
+| 0.0197        | 8.0   | 1128 | 0.1214          | 0.7872    | 0.8282 | 0.8072 | 0.9736   |
+| 0.0197        | 9.0   | 1269 | 0.1201          | 0.7946    | 0.8190 | 0.8066 | 0.9741   |
+| 0.0197        | 10.0  | 1410 | 0.1203          | 0.7859    | 0.8221 | 0.8036 | 0.9743   |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.1.2
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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