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--- |
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tags: autonlp |
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language: en |
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widget: |
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- text: "Worry is a down payment on a problem you may never have'. Joyce Meyer. #motivation #leadership #worry" |
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datasets: |
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- tweet_eval |
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model-index: |
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- name: BERT-tweet-eval-emotion |
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results: |
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- task: |
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name: Sentiment Analysis |
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type: sentiment-analysis |
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dataset: |
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name: "tweeteval" |
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type: tweet-eval |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 81.00 |
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- name: Macro F1 |
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type: macro-f1 |
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value: 77.37 |
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- name: Weighted F1 |
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type: weighted-f1 |
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value: 80.63 |
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--- |
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# `BERT-tweet-eval-emotion` trained using autoNLP |
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- Problem type: Multi-class Classification |
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## Validation Metrics |
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- Loss: 0.5408923625946045 |
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- Accuracy: 0.8099929627023223 |
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- Macro F1: 0.7737195387641751 |
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- Micro F1: 0.8099929627023222 |
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- Weighted F1: 0.8063100677512649 |
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- Macro Precision: 0.8083955817268176 |
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- Micro Precision: 0.8099929627023223 |
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- Weighted Precision: 0.8104009668394634 |
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- Macro Recall: 0.7529197049888299 |
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- Micro Recall: 0.8099929627023223 |
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- Weighted Recall: 0.8099929627023223 |
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## Usage |
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You can use cURL to access this model: |
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``` |
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$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "Worry is a down payment on a problem you may never have'. Joyce Meyer. #motivation #leadership #worry"}' https://api-inference.huggingface.co/models/philschmid/BERT-tweet-eval-emotion |
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``` |
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Or Python API: |
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```py |
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from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline |
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model_id = 'philschmid/BERT-tweet-eval-emotion' |
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tokenizer = AutoTokenizer.from_pretrained(model_id) |
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model = AutoModelForSequenceClassification.from_pretrained(model_id) |
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classifier = pipeline('text-classification', tokenizer=tokenizer, model=model) |
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classifier("Worry is a down payment on a problem you may never have'. Joyce Meyer. #motivation #leadership #worry") |
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``` |
