End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert/distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: distilbert-base-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. -->
+
+# distilbert-base-uncased-finetuned-ner-harem
+
+This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2626
+- Precision: 0.5556
+- Recall: 0.5565
+- F1: 0.5560
+- Accuracy: 0.9336
+
+## 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: 100
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 282  | 0.3748          | 0.4065    | 0.2749 | 0.3280 | 0.9053   |
+| 0.403         | 2.0   | 564  | 0.2924          | 0.5558    | 0.4705 | 0.5096 | 0.9266   |
+| 0.403         | 3.0   | 846  | 0.2863          | 0.6589    | 0.5278 | 0.5861 | 0.9347   |
+| 0.1961        | 4.0   | 1128 | 0.2626          | 0.5556    | 0.5565 | 0.5560 | 0.9336   |
+| 0.1961        | 5.0   | 1410 | 0.2710          | 0.6279    | 0.5919 | 0.6094 | 0.9403   |
+| 0.1074        | 6.0   | 1692 | 0.3046          | 0.6699    | 0.5818 | 0.6227 | 0.9408   |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.1.2
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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runs/Oct03_02-57-32_adb383108d88/events.out.tfevents.1727924523.adb383108d88.34.1

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