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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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- precision
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- recall
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model-index:
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- name: RoBERTa-RILE
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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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# RoBERTa-RILE
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6757
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- Accuracy: 0.7350
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- F1-micro: 0.7350
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- F1-macro: 0.7241
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- F1-weighted: 0.7347
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- Precision: 0.7350
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- Recall: 0.7350
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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: 1e-05
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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-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.05
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- num_epochs: 5
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-micro | F1-macro | F1-weighted | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|:-----------:|:---------:|:------:|
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| 0.7442 | 1.0 | 1812 | 0.6827 | 0.7120 | 0.7120 | 0.7007 | 0.7126 | 0.7120 | 0.7120 |
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| 0.6447 | 2.0 | 3624 | 0.6618 | 0.7281 | 0.7281 | 0.7169 | 0.7281 | 0.7281 | 0.7281 |
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| 0.5467 | 3.0 | 5436 | 0.6657 | 0.7309 | 0.7309 | 0.7176 | 0.7295 | 0.7309 | 0.7309 |
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| 0.5179 | 4.0 | 7248 | 0.6654 | 0.7346 | 0.7346 | 0.7240 | 0.7345 | 0.7346 | 0.7346 |
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| 0.4787 | 5.0 | 9060 | 0.6757 | 0.7350 | 0.7350 | 0.7241 | 0.7347 | 0.7350 | 0.7350 |
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### Framework versions
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- Transformers 4.16.2
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- Pytorch 1.9.0+cu102
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- Datasets 1.8.0
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- Tokenizers 0.10.3
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