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

Loss: 0.7252
Model Preparation Time: 0.0016
Accuracy: 0.7297
F1 Macro: 0.7254

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: Use OptimizerNames.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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time	Accuracy	F1 Macro
No log	1.0	320	0.6796	0.0016	0.7188	0.7131
0.9005	2.0	640	0.6630	0.0016	0.7438	0.7456
0.9005	3.0	960	0.6307	0.0016	0.7453	0.7447
0.537	4.0	1280	0.6060	0.0016	0.7734	0.7699
0.3829	5.0	1600	0.6971	0.0016	0.7297	0.7317
0.3829	6.0	1920	0.6877	0.0016	0.7625	0.7634

Framework versions

Transformers 4.48.2
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0

msab97/distilbert-finetuning-italian

distilbert-finetuning-italian

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

msab97/
distilbert-finetuning-italian