|
--- |
|
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/roberta-base-emotion |
|
results: |
|
- task: |
|
type: text-classification |
|
name: Text Classification |
|
dataset: |
|
name: emotion |
|
type: emotion |
|
config: default |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 0.931 |
|
name: Accuracy |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZjg5OTI4ZTlkY2VmZjYzNGEzZGQ3ZjczYzY5YjJmMGVmZDQ4ZWNiYTAyZTJiZjlmMTU2MjE1NTllMWFhYzU0MiIsInZlcnNpb24iOjF9.dc44cEsbu900M2s64GyVIWKPagBzwI-dPlfvh0NGyJFMGKOcypke9P2ary9fBZITrH3UF6lza3sCh7vWYZFHBQ |
|
- type: precision |
|
value: 0.9168321948556312 |
|
name: Precision Macro |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiN2EzYTcxNTExNGU1MmFiZjE3NGE5MDIyMDU2M2U3OGExOTdjZDE5YWU2NDhmOTJlYWMzY2NkN2U5MmRmZTE0MiIsInZlcnNpb24iOjF9.4U7vJ3ALdUUxySMhVeb4Qa1tSp3wphSIZkRYNMujz-KrOZW8kkcmCde3ioStBg3Qqyf1powYd88uk1R7DuWRBA |
|
- type: precision |
|
value: 0.931 |
|
name: Precision Micro |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMjhmZGRlYWE5ZTAzMmJiMzlmMWZiM2VlYjdiNzI0NjVmN2M2YzcxM2EzYTg0OTFiZTE1MjVmNzE5NGEzYTg2ZCIsInZlcnNpb24iOjF9.8eCHAK0rlZWnhBNQdh9kcuAeItmDUAgK3KkZ7eC-GyYhi4HT5dZiS6btcC5EjkYVOS4czcjzqxfVz4PuZgtLDQ |
|
- type: precision |
|
value: 0.9357445689014415 |
|
name: Precision Weighted |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMDhhZTdkNzYzMjhjZjc4MTAxNWZiYjgzMjhhNjRiZWRmYjc5YTA0NTQ1MzllMTYxMTVkMDk4OTE0ZGEyMTNhMiIsInZlcnNpb24iOjF9.YIZfj2Eo1nMX2GVSfqJy-Cp7VBubfUh2LuOnU60sG5Lci8FdlNbAanS1IzAyxU3U29lqiTasxfS_yrwAj5cmBQ |
|
- type: recall |
|
value: 0.8743657671177089 |
|
name: Recall Macro |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiM2Y2YTcyNzMwYzZiMmM1Yzc4YWZhNDM3ZDQyMjI1NWZhMjQyNmU5NTA0YmE2ZDBiZmY1MmUyZWRlMjRhMjFmYSIsInZlcnNpb24iOjF9.XKlFy_Cx4T4l7Otd8aAwWcI-fJ_dJ6V1Kp3uZm6OWjwCb1Do6mSdPFfwiMeBZZyfEIsNBnguegssZvHsOfTSAQ |
|
- type: recall |
|
value: 0.931 |
|
name: Recall Micro |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNzgzN2JkNzAzZDRjNjJmZjNkY2RmYzVkMWEzYTMzZDU4NzJlYzBmOWE4MTU0MGU0MTJhM2JjZDdjODhlZDExOCIsInZlcnNpb24iOjF9.9tSVB4yNBdFXpH3equwo1ZaEnVUktO6lm93UEJ-luKhxo6wgS54OLjgDq7IpJYwa3lvYyjy-sxzQEe9ri31WAg |
|
- type: recall |
|
value: 0.931 |
|
name: Recall Weighted |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMGVhZTIyMmVmOTU1YWNjMmZiZjNmOTNlNzlhZTk3NjhlZmMwZGFkZWQxZTlhZWUwZGQyN2JhOWQyNWQ3MTVhOCIsInZlcnNpb24iOjF9.2odv2fK7zH0_S_7wC3obONzjxOipDdjWvddhnGdMnrIN6CiZwLp7XgizpqcWbwAQ_9YJwjC-6wXpbq2jTvN0Bw |
|
- type: f1 |
|
value: 0.8821236522209227 |
|
name: F1 Macro |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDI0YTUxOTA2M2ZjNGM1OTJlZDAzZTAxNTg4YjY3OWNmMjNmMTk0YWRjZTE2Y2ZmYWI1ZmU3ZmJmNzNjMjBlOCIsInZlcnNpb24iOjF9.P5-TbuEUrCtX9H7F-tKn8LI1RBPhoJwjJm_l853WTSzdLioThAtIK5HBG0xgXT2uB0Q8v94qH2b8cz1j_WonDg |
|
- type: f1 |
|
value: 0.931 |
|
name: F1 Micro |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYjNmNDgyMmFjODYwNjcwOTJiOGM2N2YwYjUyMDk5Yjk2Y2I3NmFmZGFhYjU0NGM2OGUwZmRjNjcxYTU3YzgzNSIsInZlcnNpb24iOjF9.2ZoRJwQWVIcl_Ykxce1MnZ3mSxBGxGeNYFPxt9mivo9yTi3gUE7ua6JRpVEOnOUbevlWxVkUUNnmOPFqBN1sCQ |
|
- type: f1 |
|
value: 0.9300782840205046 |
|
name: F1 Weighted |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMGE1OTcxNmNmMjQ3ZDAzYzk0N2Q1MGFjM2VhNWMyYmRjY2E3ZThjODExOTNlNWMxYzdlMWM2MDBiMTZhY2M2OSIsInZlcnNpb24iOjF9.r63SEArCiFB5m0ccV2q_t5uSOtjVnWdz4PfvCYUchm0JlrRC9YAm5oWKeO419wdyFY4rZFe014yv7sRcV-CgBQ |
|
- type: loss |
|
value: 0.15155883133411407 |
|
name: loss |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiN2M4MmVlNjAzZjhiMWJlNWQxMDg5ZTRiYjFlZGYyMGMyYzU4M2IwY2E1M2E2MzA5NmU5ZjgwZTZmMDI5YjgzMyIsInZlcnNpb24iOjF9.kjgFJohkTxLKtzHJDlBvd6qolGQDSZLbrDE7C07xNGmarhTLc_A3MmLeC4MmQGOl1DxfnHflImIkdqPylyylDA |
|
--- |
|
# robert-base-emotion |
|
|
|
## Model description: |
|
[roberta](https://arxiv.org/abs/1907.11692) is Bert with better hyperparameter choices so they said it's Robustly optimized Bert during pretraining. |
|
|
|
[roberta-base](https://huggingface.co/roberta-base) finetuned on the emotion dataset using HuggingFace Trainer with below Hyperparameters |
|
``` |
|
learning rate 2e-5, |
|
batch size 64, |
|
num_train_epochs=8, |
|
``` |
|
|
|
## 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 | |
|
|
|
## How to Use the model: |
|
```python |
|
from transformers import pipeline |
|
classifier = pipeline("text-classification",model='bhadresh-savani/roberta-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': 0.002281982684507966}, |
|
{'label': 'joy', 'score': 0.9726489186286926}, |
|
{'label': 'love', 'score': 0.021365027874708176}, |
|
{'label': 'anger', 'score': 0.0026395076420158148}, |
|
{'label': 'fear', 'score': 0.0007162453257478774}, |
|
{'label': 'surprise', 'score': 0.0003483477921690792} |
|
]] |
|
""" |
|
``` |
|
|
|
## Dataset: |
|
[Twitter-Sentiment-Analysis](https://huggingface.co/nlp/viewer/?dataset=emotion). |
|
|
|
## Training procedure |
|
[Colab Notebook](https://github.com/bhadreshpsavani/ExploringSentimentalAnalysis/blob/main/SentimentalAnalysisWithDistilbert.ipynb) |
|
follow the above notebook by changing the model name to roberta |
|
|
|
## Eval results |
|
```json |
|
{ |
|
'test_accuracy': 0.9395, |
|
'test_f1': 0.9397328860104454, |
|
'test_loss': 0.14367154240608215, |
|
'test_runtime': 10.2229, |
|
'test_samples_per_second': 195.639, |
|
'test_steps_per_second': 3.13 |
|
} |
|
``` |
|
|
|
## Reference: |
|
* [Natural Language Processing with Transformer By Lewis Tunstall, Leandro von Werra, Thomas Wolf](https://learning.oreilly.com/library/view/natural-language-processing/9781098103231/) |
