model – AI Model by MohammadZalloum | AlphaNeural AI

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MohammadZalloum/
model

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

text-embeddings-inference

endpoints_compatible

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model

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.8841
Accuracy: 0.6468
Macro F1: 0.6422

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: 8
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Macro F1
0.8086	1.0	374	0.8247	0.5906	0.5943
0.6803	2.0	748	0.7970	0.6294	0.6265
0.6311	3.0	1122	0.8426	0.6401	0.6267
0.4884	4.0	1496	0.8841	0.6468	0.6422

Framework versions

Transformers 4.49.0
Pytorch 2.13.0+cu130
Datasets 2.21.0
Tokenizers 0.21.4