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--- |
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language: |
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- en |
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thumbnail: https://avatars3.githubusercontent.com/u/32437151?s=460&u=4ec59abc8d21d5feea3dab323d23a5860e6996a4&v=4 |
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tags: |
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- text-classification |
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- emotion |
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- pytorch |
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license: apache-2.0 |
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datasets: |
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- emotion |
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metrics: |
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- Accuracy, F1 Score |
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--- |
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# Albert-base-v2-emotion |
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## Model description: |
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[Albert](https://arxiv.org/pdf/1909.11942v6.pdf) is A Lite BERT architecture that has significantly fewer parameters than a traditional BERT architecture. |
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[Albert-base-v2](https://huggingface.co/albert-base-v2) finetuned on the emotion dataset using HuggingFace Trainer with below Hyperparameters |
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``` |
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learning rate 2e-5, |
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batch size 64, |
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num_train_epochs=8, |
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``` |
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## Model Performance Comparision on Emotion Dataset from Twitter: |
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| Model | Accuracy | F1 Score | Test Sample per Second | |
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| --- | --- | --- | --- | |
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| [Distilbert-base-uncased-emotion](https://huggingface.co/bhadresh-savani/distilbert-base-uncased-emotion) | 93.8 | 93.79 | 398.69 | |
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| [Bert-base-uncased-emotion](https://huggingface.co/bhadresh-savani/bert-base-uncased-emotion) | 94.05 | 94.06 | 190.152 | |
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| [Roberta-base-emotion](https://huggingface.co/bhadresh-savani/roberta-base-emotion) | 93.95 | 93.97| 195.639 | |
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| [Albert-base-v2-emotion](https://huggingface.co/bhadresh-savani/albert-base-v2-emotion) | 93.6 | 93.65 | 182.794 | |
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## How to Use the model: |
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```python |
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from transformers import pipeline |
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classifier = pipeline("text-classification",model='bhadresh-savani/albert-base-v2-emotion', return_all_scores=True) |
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prediction = classifier("I love using transformers. The best part is wide range of support and its easy to use", ) |
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print(prediction) |
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""" |
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Output: |
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[[ |
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{'label': 'sadness', 'score': 0.010403595864772797}, |
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{'label': 'joy', 'score': 0.8902180790901184}, |
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{'label': 'love', 'score': 0.042532723397016525}, |
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{'label': 'anger', 'score': 0.041297927498817444}, |
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{'label': 'fear', 'score': 0.011772023513913155}, |
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{'label': 'surprise', 'score': 0.0037756056990474463} |
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]] |
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""" |
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``` |
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## Dataset: |
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[Twitter-Sentiment-Analysis](https://huggingface.co/nlp/viewer/?dataset=emotion). |
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## Training procedure |
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[Colab Notebook](https://github.com/bhadreshpsavani/ExploringSentimentalAnalysis/blob/main/SentimentalAnalysisWithDistilbert.ipynb) |
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## Eval results |
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```json |
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{ |
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'test_accuracy': 0.936, |
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'test_f1': 0.9365658988006296, |
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'test_loss': 0.15278364717960358, |
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'test_runtime': 10.9413, |
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'test_samples_per_second': 182.794, |
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'test_steps_per_second': 2.925 |
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} |
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``` |
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## Reference: |
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* [Natural Language Processing with Transformer By Lewis Tunstall, Leandro von Werra, Thomas Wolf](https://learning.oreilly.com/library/view/natural-language-processing/9781098103231/) |
