emotion_roberta_weighted – AI Model by bellinghesam | AlphaNeural AI

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bellinghesam/
emotion_roberta_weighted

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text-classification

generated_from_trainer

FacebookAI/roberta-base

endpoints_compatible

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emotion_roberta_weighted

This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2212
Accuracy: 0.9315
Precision: 0.9388
Recall: 0.9315
F1: 0.9331

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.2588	1.0	1000	0.2401	0.9185	0.9285	0.9185	0.9208
0.1856	2.0	2000	0.2177	0.9285	0.9348	0.9285	0.9300
0.144	3.0	3000	0.1773	0.928	0.9377	0.928	0.9301
0.1139	4.0	4000	0.2212	0.9315	0.9388	0.9315	0.9331
0.0937	5.0	5000	0.2179	0.9295	0.9349	0.9295	0.9310

Framework versions

Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1