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---
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license: mit
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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-base_single_finetuned_on_cedr_augmented
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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-base_single_finetuned_on_cedr_augmented
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4650
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- Accuracy: 0.8820
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- F1: 0.8814
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- Precision: 0.8871
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- Recall: 0.8820
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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: 0.0001
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- train_batch_size: 64
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- eval_batch_size: 64
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
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- lr_scheduler_type: linear
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- num_epochs: 20
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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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| 0.8868 | 1.0 | 69 | 0.4939 | 0.8403 | 0.8376 | 0.8431 | 0.8403 |
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| 0.4248 | 2.0 | 138 | 0.3969 | 0.8779 | 0.8768 | 0.8798 | 0.8779 |
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| 0.3197 | 3.0 | 207 | 0.4019 | 0.8758 | 0.8757 | 0.8758 | 0.8758 |
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| 0.2737 | 4.0 | 276 | 0.3915 | 0.8831 | 0.8827 | 0.8847 | 0.8831 |
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| 0.2053 | 5.0 | 345 | 0.4445 | 0.8643 | 0.8650 | 0.8714 | 0.8643 |
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| 0.1705 | 6.0 | 414 | 0.4650 | 0.8820 | 0.8814 | 0.8871 | 0.8820 |
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### Framework versions
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- Transformers 4.20.1
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- Pytorch 1.11.0+cu113
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- Datasets 2.3.2
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- Tokenizers 0.12.1
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