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README.md
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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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- f1
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model-index:
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- name: BiBert-Subjectivity
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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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# BiBert-Subjectivity
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This model is a fine-tuned version of [nlptown/bert-base-multilingual-uncased-sentiment](https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1481
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- Accuracy: 0.9583
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- F1: 0.9581
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- Mae: 0.0417
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- Accuracy 2: 0.9583
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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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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Mae | Accuracy 2 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-----:|:----------:|
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| No log | 1.0 | 112 | 0.1333 | 0.95 | 0.9508 | 0.05 | 0.95 |
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| No log | 2.0 | 224 | 0.1517 | 0.953 | 0.9531 | 0.047 | 0.953 |
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| No log | 3.0 | 336 | 0.2219 | 0.951 | 0.9505 | 0.049 | 0.951 |
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| No log | 4.0 | 448 | 0.2327 | 0.947 | 0.9479 | 0.053 | 0.947 |
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| 0.0865 | 5.0 | 560 | 0.2557 | 0.953 | 0.9528 | 0.047 | 0.953 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.0+cu116
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- Datasets 2.8.0
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- Tokenizers 0.13.2
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