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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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- f1
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- recall
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- accuracy
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model-index:
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- name: RoBERTa-THESIS
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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-THESIS
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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: 1.1698
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- F1: 0.7701
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- Recall: 0.7701
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- Accuracy: 0.7701
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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: 32
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- eval_batch_size: 32
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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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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|
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| 0.9918 | 1.0 | 1446 | 0.8174 | 0.7433 | 0.7433 | 0.7433 |
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| 0.7223 | 2.0 | 2892 | 0.7799 | 0.7618 | 0.7618 | 0.7618 |
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| 0.5389 | 3.0 | 4338 | 0.7730 | 0.7716 | 0.7716 | 0.7716 |
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| 0.4073 | 4.0 | 5784 | 0.8121 | 0.7737 | 0.7737 | 0.7737 |
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| 0.2985 | 5.0 | 7230 | 0.8841 | 0.7697 | 0.7697 | 0.7697 |
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| 0.2233 | 6.0 | 8676 | 0.9573 | 0.7717 | 0.7717 | 0.7717 |
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| 0.1679 | 7.0 | 10122 | 1.0132 | 0.7721 | 0.7721 | 0.7721 |
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| 0.1233 | 8.0 | 11568 | 1.0948 | 0.7691 | 0.7691 | 0.7691 |
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| 0.096 | 9.0 | 13014 | 1.1502 | 0.7689 | 0.7689 | 0.7689 |
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| 0.0799 | 10.0 | 14460 | 1.1698 | 0.7701 | 0.7701 | 0.7701 |
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### Framework versions
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- Transformers 4.28.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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