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eng.rst.rstdt_distilbert-base-uncased_seg_4_0.00002 – AI Model by kloee | AlphaNeural AI

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kloee/
eng.rst.rstdt_distilbert-base-uncased_seg_4_0.00002

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token-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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eng.rst.rstdt_distilbert-base-uncased_seg_4_0.00002

This model is a fine-tuned version of distilbert-base-uncased on the generator 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: 2e-05
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use 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: 2

Training results

Framework versions

Transformers 4.48.0.dev0
Pytorch 2.3.0a0+ebedce2
Datasets 3.0.0
Tokenizers 0.21.0