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README.md
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---
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library_name: transformers
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license: mit
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base_model: FacebookAI/xlm-roberta-base
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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- precision
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- recall
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model-index:
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- name: xlm-roberta-reddit-5
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# xlm-roberta-reddit-5
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4454
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- Accuracy: 0.8677
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- F1: 0.8380
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- Precision: 0.8594
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- Recall: 0.8353
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 12
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- eval_batch_size: 12
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| No log | 1.0 | 74 | 1.0770 | 0.5185 | 0.3072 | 0.2694 | 0.3933 |
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| No log | 2.0 | 148 | 0.8862 | 0.6667 | 0.4737 | 0.4204 | 0.5580 |
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| No log | 3.0 | 222 | 0.6454 | 0.7143 | 0.5819 | 0.7749 | 0.6237 |
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| No log | 4.0 | 296 | 0.4804 | 0.8360 | 0.7701 | 0.8185 | 0.7899 |
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| No log | 5.0 | 370 | 0.4454 | 0.8677 | 0.8380 | 0.8594 | 0.8353 |
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### Framework versions
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- Transformers 4.48.3
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- Pytorch 2.6.0+cu124
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- Datasets 3.4.0
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- Tokenizers 0.21.1
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