Hugging Face's logo

bhadresh-savani
/
electra-base-emotion

Text Classification Transformers PyTorch TensorFlow JAX
English electra emotion Eval Results Inference Endpoints
Model card Files Community
4
electra-base-emotion / README.md
bhadresh-savani's picture
bhadresh-savani
Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluator (#2)
8852981
preview code
|
raw history blame contribute delete
No virus
6.5 kB
metadata
language:
  - en
license: apache-2.0
tags:
  - text-classification
  - emotion
  - pytorch
datasets:
  - emotion
metrics:
  - Accuracy, F1 Score
thumbnail: >-
  https://avatars3.githubusercontent.com/u/32437151?s=460&u=4ec59abc8d21d5feea3dab323d23a5860e6996a4&v=4
model-index:
  - name: bhadresh-savani/electra-base-emotion
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: emotion
          type: emotion
          config: default
          split: test
        metrics:
          - type: accuracy
            value: 0.9265
            name: Accuracy
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMjYwNGQxMzRmMjViNzVhODJjM2UxOGNkYmNjOTE3OTczNzUxN2IyNGY1ZmFiY2VlNzNkOWY3M2I5YmZlNDlmMyIsInZlcnNpb24iOjF9.4e7MLUVHIBXYIwOgAcSDRJ7ziMXMSwk2-Ip8DH1RjxBDthc4MiBglMxbOUUjSzTPtSSEZKqfTZonUq7yR_rwBQ
          - type: precision
            value: 0.911532655431019
            name: Precision Macro
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNzFkYzRjZGUwYmJmNmUxYjM3NzY3NWY0NzBhZjU5MDQxZWY4ZjA3OWMwMjQxMWJlODg5ZjIxZWFhYTg0ZGY2NCIsInZlcnNpb24iOjF9.I0j92y0SToxjoKkKX7AD8h5p3pDePSdQwOCBeZj-OGF0MRBeqo1Ejg-1snFFplU0mtoFF6rCvRq9WosqvRhfCA
          - type: precision
            value: 0.9265
            name: Precision Micro
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNGE2YzUyN2ZhYTdjZjQ4OWVkN2M4MzhjZWM0YzAyYWU2YjllZDYzOTYxYTZlZDAxNjA4ODY5NTk1MmE3ODQwZiIsInZlcnNpb24iOjF9.VQSaLzlreAIfy0iDJsCo-Mg1xF4gMv-KQkeIzoTKLhyp3V7rn5d5oaD8EEsay3gDamSC-xj8LndOqFL1AokZCg
          - type: precision
            value: 0.9305456360257519
            name: Precision Weighted
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNjcyZDdjMWE5YzhlNWUyZDg5YWUwOGRkYWFiMDNmMTY4N2QxZDg1YTU0MGQ2ZWI1ZDI5Mjk2MTVmN2JmZTA1YiIsInZlcnNpb24iOjF9.EvcL-mfmJ3rGQCaVRejoWplButUT_dQjgwPw-rWlqSC7Ex3reLa3hQ9PtYuXtYM3ymVl77rFgW2Yxf3lIn6RBg
          - type: recall
            value: 0.8536923122511134
            name: Recall Macro
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNjIwNjU1ZmIwYzgyYzNmNmY2NDkyNjA2MDg0NDcxOWQwMmJmZTFlYzg0NjI0YWMxNzhmYTQwNzU0Yzg5ZTk4MCIsInZlcnNpb24iOjF9.8he8WOjzHqJp5h2TUig7oDrn4jwSbSB1J69fmh-2UUrpH46VpwxD5bO0MG3Nm4HHYK2ZIzPb-sTX7hhMJHM7Bw
          - type: recall
            value: 0.9265
            name: Recall Micro
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZjRiODljZTc0ZDU3YWNlZTRlYjQwY2M5YWFiY2VkOWM5Yjg5NjYzZTNkYTA1ZTc3ZjU3YjY3ZGMzNWFiNTNhNSIsInZlcnNpb24iOjF9.W74pDxOq18_Wr3Mmd0f1whXMJuVT3DhmYCWh3Z_VKB6QMSgNUf4l1iBYukIT8Lrwr50z4pscBGY3YktlUgg5Bg
          - type: recall
            value: 0.9265
            name: Recall Weighted
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMjgxNDhjMDcwZTA2ZWQ2NTFlMTFjOGU4NDE4ZDY0MDJjNGMwOGYzMDViYTM5Y2M5ZTc2NDM3OTdmYTc1NzhhMiIsInZlcnNpb24iOjF9.x4sUtEJWliLYqyKkKMEvb10lSxqN8vhrmSAnwtyCp0tEag6DUNEUA6_nojaC3ABIDb4ZwVd7JIcQ5yD2PKU-Dg
          - type: f1
            value: 0.8657529340483895
            name: F1 Macro
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZmUzZjNiOTZhNjE0ZWE5NDI2NzBmOGViYTc0NWYwYWQ3ZjA1ZTE1NmM5ZWRiZjA0NGYyZDM2OWE5YzA4NDY1MyIsInZlcnNpb24iOjF9.OLYrJI7nW4-nvCbEsJDIwyGL9lI1UNM-TBpMmosbkUCLu8MhhCdMo0tdKRaCRoDUtfLlwcUG9mOayAsDdfrqCw
          - type: f1
            value: 0.9265
            name: F1 Micro
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZWE1ZDI1MzA3YTcwODU0NTgxYTNmYjc5ZDZkYzI3OWZmYjNlNjI5OWI4MDE4NDRhOWMyNWZiMjZlMTIwNWU3YSIsInZlcnNpb24iOjF9.ZpLdxeqJjKiLxUxRIVbBZa9u5w0UMPKVwvOha4tHMTiyq3RaW8TNOkFdO7TIsgxoPdQb6wzWNDojrqJOY4vsDg
          - type: f1
            value: 0.924844632421077
            name: F1 Weighted
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiY2VhNWZmM2E4NDI5NmRiMWJkNDk2MDMyMDZmYmE2ODBlNTA2NTdhYTc4NzRkOGU1ODczZDU4MTdhYTZlOTRiZCIsInZlcnNpb24iOjF9.93XiZO_2N0nLa2PU3TICEOT8HjURPzpaAVD_5e5MFMHrtMIB1Barg0cvzc3TCisKxV_vlt1i20d2YwtfWKgrBQ
          - type: loss
            value: 0.3268870413303375
            name: loss
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiM2IyMjdlMWZkNjQwNWVkYzU1MWYyODJkMzAwOWJmZWJiYTI0OGRlZjhkMmZkN2JhMjJmMDdkMzQ1Y2U3NDY3MyIsInZlcnNpb24iOjF9.aEnyBFvFKixU1zh5GYkIUDcf4uD6PV7pESdbdvG_oJ1lIisOg6CEb6nekcYtDebcoL3q1cbrBdhgK6dgdShJBQ

Electra-base-emotion

Model description:

Model Performance Comparision on Emotion Dataset from Twitter:

Model Accuracy F1 Score Test Sample per Second
Distilbert-base-uncased-emotion 93.8 93.79 398.69
Bert-base-uncased-emotion 94.05 94.06 190.152
Roberta-base-emotion 93.95 93.97 195.639
Albert-base-v2-emotion 93.6 93.65 182.794
Electra-base-emotion 91.95 91.90 472.72

How to Use the model: 

from transformers import pipeline
classifier = pipeline("text-classification",model='bhadresh-savani/electra-base-emotion', return_all_scores=True)
prediction = classifier("I love using transformers. The best part is wide range of support and its easy to use", )
print(prediction)

"""
Output:
[[
{'label': 'sadness', 'score': 0.0006792712374590337}, 
{'label': 'joy', 'score': 0.9959300756454468}, 
{'label': 'love', 'score': 0.0009452480007894337}, 
{'label': 'anger', 'score': 0.0018055217806249857}, 
{'label': 'fear', 'score': 0.00041110432357527316}, 
{'label': 'surprise', 'score': 0.0002288572577526793}
]]
"""

Dataset:

Twitter-Sentiment-Analysis.

Training procedure

Colab Notebook

Eval results 

{
 'epoch': 8.0,
 'eval_accuracy': 0.9195,
 'eval_f1': 0.918975455617076,
 'eval_loss': 0.3486028015613556,
 'eval_runtime': 4.2308,
 'eval_samples_per_second': 472.726,
 'eval_steps_per_second': 7.564
 }

Reference: