my_awesome_id_nergrit_corpus_model

This model is a fine-tuned version of distilbert-base-uncased on the id_nergrit_corpus dataset. It achieves the following results on the evaluation set:

• Loss: 0.3602
• Precision: 0.6222
• Recall: 0.6439
• F1: 0.6329
• Accuracy: 0.9038

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	Precision	Recall	F1	Accuracy
0.9117	1.0	784	0.4198	0.5691	0.5948	0.5817	0.8893
0.4089	2.0	1568	0.3602	0.6222	0.6439	0.6329	0.9038

Framework versions

• Transformers 4.33.2
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3