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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: finetuned-Sentiment-classfication-ROBERTA-model |
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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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# finetuned-Sentiment-classfication-ROBERTA-model |
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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: 0.6147 |
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- Rmse: 0.6327 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 64 |
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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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| 0.6405 | 4.0 | 500 | 0.6147 | 0.6327 | |
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| 0.2214 | 8.0 | 1000 | 0.8795 | 0.6251 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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