Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluator (#2)

8852981 about 1 year ago

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6.5 kB

	---
	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](https://huggingface.co/bhadresh-savani/distilbert-base-uncased-emotion) \| 93.8 \| 93.79 \| 398.69 \|
	\| [Bert-base-uncased-emotion](https://huggingface.co/bhadresh-savani/bert-base-uncased-emotion) \| 94.05 \| 94.06 \| 190.152 \|
	\| [Roberta-base-emotion](https://huggingface.co/bhadresh-savani/roberta-base-emotion) \| 93.95 \| 93.97\| 195.639 \|
	\| [Albert-base-v2-emotion](https://huggingface.co/bhadresh-savani/albert-base-v2-emotion) \| 93.6 \| 93.65 \| 182.794 \|
	\| [Electra-base-emotion](https://huggingface.co/bhadresh-savani/electra-base-emotion) \| 91.95 \| 91.90 \| 472.72 \|

	## How to Use the model:
	```python
	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](https://huggingface.co/nlp/viewer/?dataset=emotion).

	## Training procedure
	[Colab Notebook](https://github.com/bhadreshpsavani/ExploringSentimentalAnalysis/blob/main/SentimentalAnalysisWithDistilbert.ipynb)

	## Eval results
	```json
	{
	'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:
	* [Natural Language Processing with Transformer By Lewis Tunstall, Leandro von Werra, Thomas Wolf](https://learning.oreilly.com/library/view/natural-language-processing/9781098103231/)