End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: gpt2
+tags:
+- generated_from_trainer
+datasets:
+- hatexplain
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: finetuned-gpt2-hatexplainV2
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: hatexplain
+      type: hatexplain
+      config: plain_text
+      split: validation
+      args: plain_text
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.6787941787941788
+    - name: Precision
+      type: precision
+      value: 0.6744852177618593
+    - name: Recall
+      type: recall
+      value: 0.6787941787941788
+    - name: F1
+      type: f1
+      value: 0.6752460830597729
+---
+
+<!-- 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. -->
+
+# finetuned-gpt2-hatexplainV2
+
+This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the hatexplain dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8927
+- Accuracy: 0.6788
+- Precision: 0.6745
+- Recall: 0.6788
+- F1: 0.6752
+
+## 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: 3e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use OptimizerNames.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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.7476        | 1.0   | 962  | 0.7423          | 0.6785   | 0.6724    | 0.6785 | 0.6695 |
+| 0.6276        | 2.0   | 1924 | 0.7384          | 0.6878   | 0.6798    | 0.6878 | 0.6815 |
+| 0.5859        | 3.0   | 2886 | 0.7771          | 0.6790   | 0.6774    | 0.6790 | 0.6762 |
+| 0.3921        | 4.0   | 3848 | 0.8746          | 0.6795   | 0.6752    | 0.6795 | 0.6768 |
+| 0.4358        | 5.0   | 4810 | 0.9455          | 0.6769   | 0.6724    | 0.6769 | 0.6739 |
+
+
+### Framework versions
+
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu118
+- Datasets 3.1.0
+- Tokenizers 0.21.0