End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: FacebookAI/xlm-roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: xlm-roberta-reddit-10
+  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. -->
+
+# xlm-roberta-reddit-10
+
+This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7624
+- Accuracy: 0.7675
+- F1: 0.7491
+- Precision: 0.7711
+- Recall: 0.7457
+
+## 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: 2e-05
+- train_batch_size: 12
+- eval_batch_size: 12
+- 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 | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| No log        | 1.0   | 123  | 1.5725          | 0.4236   | 0.2919 | 0.2961    | 0.339  |
+| No log        | 2.0   | 246  | 1.1745          | 0.6051   | 0.4965 | 0.6084    | 0.5353 |
+| No log        | 3.0   | 369  | 0.9715          | 0.7166   | 0.6859 | 0.7459    | 0.6734 |
+| No log        | 4.0   | 492  | 0.7882          | 0.7834   | 0.7679 | 0.7870    | 0.7656 |
+| 1.3067        | 5.0   | 615  | 0.7624          | 0.7675   | 0.7491 | 0.7711    | 0.7457 |
+
+
+### Framework versions
+
+- Transformers 4.48.3
+- Pytorch 2.6.0+cu124
+- Datasets 3.4.0
+- Tokenizers 0.21.1

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