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Nit-Ram-toxicidad – AI Model by Nit-Ram | AlphaNeural AI

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Nit-Ram/
Nit-Ram-toxicidad

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

text-embeddings-inference

endpoints_compatible

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Nit-Ram-toxicidad

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.

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: 5e-05
train_batch_size: 16
eval_batch_size: 64
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: 500
num_epochs: 5

Training results

Framework versions

Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2