SamLowe/roberta-base-go_emotions
text-classification model by SamLowe
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Model card & documentation
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Model trained from roberta-base on the goemotions dataset for multi-label classification. A version of this model in ONNX format (including an INT8 quantized ONNX version) is now available at https://huggingface.co/SamLowe/roberta-base-goemotions-onnx. These are faster for inference, esp for smaller batch sizes, massively reduce the size of the dependencies required for inference, make inference of the model more multi-platform, and in the case of the quantized version reduce the model file/download size by 75% whilst retaining almost all the accuracy if you only need inference. goemotions is based on Reddit data and has 28 labels. It is a multi-label dataset where one or multiple labels may apply for any given input text, hence this model is a multi-label classification model with 28 'probability' float outputs for any given input text. Typically a threshold of 0.5 is applied to the probabilities for the prediction for each label. The model was trained using AutoModelForSequenceClassification.frompretrained…
Read the full model card ↗ · Preview checked 2026-10-31T09:25:20.763Z
Inside the original model card — Document outline
- Overview
- ONNX version also available
- Dataset used for the model
- How the model was created
- Inference
- Evaluation / metrics
- Summary
- Commentary on the dataset
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Model overview
SamLowe/roberta-base-go_emotions is a text-classification model repository published by SamLowe on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-classification
- Library
- transformers
- Recent downloads (30 days)
- 5,161,000
- Cumulative likes
- 717
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 124,667,678
- Architecture
- RobertaForSequenceClassification
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2022-09-15T13:04:21.000Z
- Last modified
- 2026-05-13T18:23:34.000Z
Compatibility and lineage
Reported languages: en
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:49:31.990Z. Daily imports are snapshots, not real-time monitoring.
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