End of training

README.md

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+---
+language:
+- tr
+license: apache-2.0
+base_model: distilbert/distilbert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- Toygar/turkish-offensive-language-detection
+metrics:
+- accuracy
+model-index:
+- name: Distilbert Base Uncased Turkish Offensive Language Classifier - Atakan Ince
+  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 Turkish Offensive Language Classifier - Atakan Ince
+
+This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the Turkish Offensive Language Dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2440
+- Accuracy: 0.9067
+
+## 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: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 4000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.3075        | 0.36  | 1000 | 0.2871          | 0.8901   |
+| 0.2652        | 0.72  | 2000 | 0.2520          | 0.9031   |
+| 0.2825        | 1.09  | 3000 | 0.2506          | 0.9007   |
+| 0.2471        | 1.45  | 4000 | 0.2440          | 0.9067   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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