mi23
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responsible_iddistilbert-base-uncased

Text Classification

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text-embeddings-inference

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responsible_iddistilbert-base-uncased

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

Loss: 2.5066
Accuracy: 0.5215

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: 160
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 12
total_train_batch_size: 1920
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 512.0

Training results

Framework versions

Transformers 4.32.0
Pytorch 2.0.1
Datasets 2.14.4
Tokenizers 0.13.3

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