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distilbert-ft-test3

This model is a fine-tuned version of distilbert-base-uncased on thomasavare/waste-classification-v2. It is part of my master thesis at Politecnico di Torino in partenership with ReLearn.

It achieves the following results on the test set:

Model description

DistilBERT finetuned for waste classification on 50 different classes as part of my master thesis at Politecnico di Torino.

Intended uses & limitations

Use for waste classification on 50 different waste classes (see dataset)

Training and evaluation data

waste-classification-v2 dataset

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 5e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
• training_precision: float32

Training results

Framework versions

• Transformers 4.28.1
• TensorFlow 2.12.0
• Datasets 2.12.0
• Tokenizers 0.13.3