End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: AnonymousCS/populism_english_bert_base_cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: populism_model171
+  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. -->
+
+# populism_model171
+
+This model is a fine-tuned version of [AnonymousCS/populism_english_bert_base_cased](https://huggingface.co/AnonymousCS/populism_english_bert_base_cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3850
+- Accuracy: 0.9554
+- 1-f1: 0.52
+- 1-recall: 0.6842
+- 1-precision: 0.4194
+- Balanced Acc: 0.8248
+
+## 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: 64
+- eval_batch_size: 64
+- 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: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1   | 1-recall | 1-precision | Balanced Acc |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
+| 0.2183        | 1.0   | 34   | 0.2820          | 0.9257   | 0.4118 | 0.7368   | 0.2857      | 0.8347       |
+| 0.1671        | 2.0   | 68   | 0.3673          | 0.9480   | 0.4815 | 0.6842   | 0.3714      | 0.8209       |
+| 0.0818        | 3.0   | 102  | 0.3850          | 0.9554   | 0.52   | 0.6842   | 0.4194      | 0.8248       |
+
+
+### Framework versions
+
+- Transformers 4.49.0.dev0
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

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