hbtn_emotion_classifier – AI Model by layka123 | AlphaNeural AI

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layka123/
hbtn_emotion_classifier

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

text-embeddings-inference

endpoints_compatible

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hbtn_emotion_classifier

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

Loss: 0.2261
Accuracy: 0.9325
Precision: 0.9366
Recall: 0.9325
F1: 0.9335

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: 32
seed: 0
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
0.2452	1.0	1000	0.1764	0.9325	0.9363	0.9325	0.9335
0.1536	2.0	2000	0.1605	0.939	0.9424	0.939	0.9391
0.1103	3.0	3000	0.1790	0.935	0.9363	0.935	0.9352
0.0794	4.0	4000	0.1904	0.9395	0.9420	0.9395	0.9400
0.0597	5.0	5000	0.1911	0.94	0.9405	0.94	0.9399

Framework versions

Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1