End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert/distilroberta-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: distilroberta-base-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. -->
+
+# distilroberta-base-finetuned-ner-harem
+
+This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1882
+- Precision: 0.6628
+- Recall: 0.6836
+- F1: 0.6730
+- 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: 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  | 0.2799          | 0.4758    | 0.4403 | 0.4574 | 0.9202   |
+| 0.3348        | 2.0   | 564  | 0.2225          | 0.5810    | 0.5940 | 0.5875 | 0.9396   |
+| 0.3348        | 3.0   | 846  | 0.2105          | 0.6015    | 0.6149 | 0.6081 | 0.9389   |
+| 0.1571        | 4.0   | 1128 | 0.1979          | 0.6732    | 0.6642 | 0.6687 | 0.9534   |
+| 0.1571        | 5.0   | 1410 | 0.1882          | 0.6628    | 0.6836 | 0.6730 | 0.9512   |
+| 0.0948        | 6.0   | 1692 | 0.2099          | 0.6196    | 0.6612 | 0.6397 | 0.9495   |
+| 0.0948        | 7.0   | 1974 | 0.2251          | 0.6900    | 0.6776 | 0.6837 | 0.9540   |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.1.2
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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runs/Oct03_02-47-53_c6e44a1eeb1e/events.out.tfevents.1727923957.c6e44a1eeb1e.34.3

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