distilbert_base_multilingual_cased_ru_action_min_chunks_works_19_12

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

• Train Loss: 0.0535
• Validation Loss: 1.3927
• Train Accuracy: 0.6869
• Epoch: 14

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:

• 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 6660, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Validation Loss	Train Accuracy	Epoch
0.6916	0.6779	0.5859	0
0.6895	0.6660	0.6162	1
0.6505	0.6476	0.6566	2
0.5595	0.6096	0.7374	3
0.4751	0.7793	0.5960	4
0.3377	0.8518	0.6768	5
0.2418	1.0199	0.6465	6
0.1604	1.1340	0.6667	7
0.1399	1.1893	0.6465	8
0.1198	0.9966	0.6465	9
0.0854	1.2855	0.6768	10
0.0747	1.2972	0.6566	11
0.0594	1.3570	0.6970	12
0.0561	1.4063	0.6566	13
0.0535	1.3927	0.6869	14

Framework versions

• Transformers 4.35.2
• TensorFlow 2.15.0
• Datasets 2.15.0
• Tokenizers 0.15.0