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---
datasets:
- go_emotions
language:
- en
library_name: transformers
model-index:
- name: text-classification-goemotions
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: go_emotions
type: multilabel_classification
config: simplified
split: test
args: simplified
metrics:
- name: F1
type: f1
value: 0.487
license: apache-2.0
tags:
- emotion
- emotions
- multi-class-classification
- multi-label-classification
---
# Text Classification GoEmotions
This model is a fined-tuned version of [MiniLMv2-L6-H384](https://huggingface.co/nreimers/MiniLMv2-L6-H384-distilled-from-RoBERTa-Large) on the on the [go_emotions](https://huggingface.co/datasets/go_emotions) dataset.
The quantized version in ONNX format can be found [here](https://huggingface.co/minuva/MiniLMv2-goemotions-v2-onnx)
# Load the Model
```py
from transformers import pipeline
pipe = pipeline(model='minuva/MiniLMv2-goemotions-v2', task='text-classification')
pipe("I am angry")
# [{'label': 'anger', 'score': 0.9722517132759094}]
```
# Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 6e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
# Metrics (comparison with teacher model)
| Teacher (params) | Student (params) | Set | Score (teacher) | Score (student) |
|--------------------|-------------|----------|--------| --------|
| tasinhoque/text-classification-goemotions (355M) | MiniLMv2-goemotions-v2 (30M) | Validation | 0.514252 |0.484898 |
| tasinhoque/text-classification-goemotions (355M) | MiniLMv2-goemotions-v2 (30M) | Test | 0.501937 | 0.486890 |
# Deployment
Check out our [fast-nlp-text-emotion repository](https://github.com/minuva/fast-nlp-text-emotion) for a FastAPI based server to easily deploy this model on CPU devices. |