
# 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.
{"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "datasets": ["go_emotions"], "model-index": [{"name": "text-classification-goemotions", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "go_emotions", "type": "multilabel_classification", "config": "simplified", "split": "test", "args": "simplified"}, "metrics": [{"type": "f1", "value": 0.487, "name": "F1"}]}]}]}
transformers safetensors roberta text-classification en dataset:go_emotions license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us