End of training

README.md

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+---
+library_name: transformers
+base_model: cardiffnlp/twitter-xlm-roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: multipride_xml_roberta
+  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. -->
+
+# multipride_xml_roberta
+
+This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3575
+- Accuracy: 0.9018
+- Precision: 0.8201
+- Recall: 0.7409
+- F1: 0.7720
+
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.3699        | 1.0   | 262  | 0.3192          | 0.8906   | 0.9149    | 0.6237 | 0.6675 |
+| 0.306         | 2.0   | 524  | 0.3669          | 0.8973   | 0.8080    | 0.7318 | 0.7616 |
+| 0.2227        | 3.0   | 786  | 0.3575          | 0.9018   | 0.8201    | 0.7409 | 0.7720 |
+
+
+### Framework versions
+
+- Transformers 4.57.2
+- Pytorch 2.9.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.1