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results – AI Model by Kimata | AlphaNeural AI

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Kimata/
results

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text-classification

generated_from_trainer

FacebookAI/roberta-base

text-embeddings-inference

endpoints_compatible

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results

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

eval_loss: 0.0172
eval_accuracy: 0.9968
eval_precision: 0.9968
eval_recall: 0.9968
eval_f1: 0.9968
eval_roc_auc: 0.9999
eval_runtime: 273.0945
eval_samples_per_second: 133.046
eval_steps_per_second: 4.16
epoch: 2.8622
step: 13000

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 with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3

Framework versions

Transformers 4.53.3
Pytorch 2.6.0+cu124
Datasets 4.4.1
Tokenizers 0.21.2