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model_23 – AI Model by kajamo | AlphaNeural AI

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kajamo/
model_23

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distilbert/distilbert-base-uncased

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model_23

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

eval_loss: 0.9889
eval_accuracy: 0.5416
eval_precision: 0.6281
eval_recall: 0.5416
eval_f1: 0.4496
eval_runtime: 42.5539
eval_samples_per_second: 287.753
eval_steps_per_second: 18.001
epoch: 1.0
step: 3062

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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 1000
num_epochs: 20
mixed_precision_training: Native AMP
label_smoothing_factor: 0.03

Framework versions

PEFT 0.11.1
Transformers 4.41.2
Pytorch 2.1.2
Datasets 2.19.2
Tokenizers 0.19.1