emotion_roberta_weighted – AI Model by MojtabaHadei | AlphaNeural AI

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MojtabaHadei/
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: 0.2605
Accuracy: 0.924
F1: 0.9254
Precision: 0.9287
Recall: 0.924

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	F1	Precision	Recall
0.2977	1.0	1000	0.2396	0.917	0.9182	0.9236	0.917
0.1983	2.0	2000	0.2199	0.93	0.9309	0.9338	0.93
0.1787	3.0	3000	0.1968	0.9325	0.9334	0.9363	0.9325
0.1374	4.0	4000	0.1888	0.937	0.9377	0.9407	0.937
0.1188	5.0	5000	0.2357	0.939	0.9397	0.9416	0.939

Framework versions

Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1