NimonikDistilBERT-multling-frenzhnl-full

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

• Loss: 0.1232
• Accuracy: 0.9623
• Macro Precision: 0.9531
• Macro Recall: 0.9534
• F Score: 0.9533

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Macro Precision	Macro Recall	F Score
0.227	1.0	14771	0.1672	0.9443	0.9361	0.9259	0.9308
0.1709	2.0	29542	0.1232	0.9623	0.9531	0.9534	0.9533

Framework versions

• Transformers 4.31.0
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.13.3