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--- |
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base_model: mastikaui/NLP-Sentiment-Analysis-Airline-Tweets-with-BERT-V2 |
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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: NLP-Sentiment-Analysis-Airline-Tweets-with-BERT-V2-tuning |
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results: [] |
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language: |
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- en |
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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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# NLP-Sentiment-Analysis-Airline-Tweets-with-BERT-V2-tuning |
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This model is a fine-tuned version of [mastikaui/NLP-Sentiment-Analysis-Airline-Tweets-with-BERT-V2](https://huggingface.co/mastikaui/NLP-Sentiment-Analysis-Airline-Tweets-with-BERT-V2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3128 |
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- Accuracy: 0.8776 |
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- F1 Score: 0.8775 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
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| 0.3035 | 1.0 | 1224 | 0.3224 | 0.8636 | 0.8637 | |
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| 0.2797 | 2.0 | 2448 | 0.3174 | 0.8685 | 0.8685 | |
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| 0.2881 | 3.0 | 3672 | 0.3139 | 0.8709 | 0.8709 | |
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| 0.2719 | 4.0 | 4896 | 0.3167 | 0.8734 | 0.8734 | |
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| 0.2573 | 5.0 | 6120 | 0.3155 | 0.8758 | 0.8758 | |
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| 0.2524 | 6.0 | 7344 | 0.3153 | 0.8743 | 0.8743 | |
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| 0.2531 | 7.0 | 8568 | 0.3158 | 0.8752 | 0.8753 | |
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| 0.2516 | 8.0 | 9792 | 0.3199 | 0.8746 | 0.8747 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
