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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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model-index:
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- name: Sentiment_Analysis_RoBERTa
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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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# Sentiment_Analysis_RoBERTa
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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: 0.5934
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- Rmse: 0.6311
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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: 3e-05
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 32
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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_steps: 500
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- num_epochs: 10
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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 | Rmse |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 0.7173 | 2.0 | 500 | 0.5934 | 0.6311 |
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| 0.4139 | 4.0 | 1000 | 0.6405 | 0.6015 |
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| 0.1956 | 6.0 | 1500 | 0.8526 | 0.6122 |
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| 0.0997 | 8.0 | 2000 | 1.1684 | 0.6089 |
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| 0.0569 | 10.0 | 2500 | 1.2575 | 0.5986 |
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### Framework versions
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- Transformers 4.29.0
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- Pytorch 2.0.0+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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