distilbert – AI Model by Esteban-Ospina | AlphaNeural AI

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Esteban-Ospina/
distilbert

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

text-embeddings-inference

endpoints_compatible

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distilbert

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: 0.6142
F1 Macro: 0.7326
Accuracy: 0.7861

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: 32
eval_batch_size: 32
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
lr_scheduler_warmup_steps: 50
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Macro	Accuracy
0.8449	1.0	102	0.7460	0.5616	0.7353
0.5523	2.0	204	0.6432	0.6725	0.7487
0.3661	3.0	306	0.6329	0.7106	0.7620
0.2955	4.0	408	0.5991	0.7412	0.7968
0.2323	5.0	510	0.6142	0.7326	0.7861

Framework versions

Transformers 5.3.0
Pytorch 2.8.0+cu128
Datasets 4.8.3
Tokenizers 0.22.2