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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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- f1
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model-index:
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- name: roberta-base-finetuned-3d-sentiment
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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-base-finetuned-3d-sentiment
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6047
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- Accuracy: 0.7713
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- Precision: 0.7719
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- Recall: 0.7713
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- F1: 0.7703
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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: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 4
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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: 6381
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- num_epochs: 7
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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 | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 0.7978 | 1.0 | 1595 | 0.7782 | 0.6953 | 0.7191 | 0.6953 | 0.6926 |
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| 0.5526 | 2.0 | 3190 | 0.6951 | 0.7229 | 0.7398 | 0.7229 | 0.7233 |
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| 0.4904 | 3.0 | 4785 | 0.6390 | 0.7388 | 0.7530 | 0.7388 | 0.7366 |
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| 0.4307 | 4.0 | 6380 | 0.6047 | 0.7713 | 0.7719 | 0.7713 | 0.7703 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu117
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- Datasets 2.10.1
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- Tokenizers 0.13.3
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