End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: AnonymousCS/populism_multilingual_roberta_base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- recall
+- precision
+model-index:
+- name: populism_model78
+  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_model78
+
+This model is a fine-tuned version of [AnonymousCS/populism_multilingual_roberta_base](https://huggingface.co/AnonymousCS/populism_multilingual_roberta_base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4741
+- Accuracy: 0.8282
+- F1: 0.2034
+- Recall: 0.5
+- Precision: 0.1277
+
+## 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: 128
+- eval_batch_size: 128
+- seed: 42
+- optimizer: Use 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
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
+| No log        | 1.0   | 18   | 0.4719          | 0.9122   | 0.1724 | 0.2083 | 0.1471    |
+| No log        | 2.0   | 36   | 0.4382          | 0.8355   | 0.2241 | 0.5417 | 0.1413    |
+| 0.4375        | 3.0   | 54   | 0.4526          | 0.8154   | 0.192  | 0.5    | 0.1188    |
+| 0.4375        | 4.0   | 72   | 0.4988          | 0.9068   | 0.2154 | 0.2917 | 0.1707    |
+| 0.4375        | 5.0   | 90   | 0.4741          | 0.8282   | 0.2034 | 0.5    | 0.1277    |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

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