mdeberta-v3-base-subjectivity-bulgarian

This model is a fine-tuned version of microsoft/mdeberta-v3-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.5111
• Macro F1: 0.7869
• Macro P: 0.7949
• Macro R: 0.7839
• Subj F1: 0.7510
• Subj P: 0.8033
• Subj R: 0.7050
• Accuracy: 0.7930

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: 1e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use 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: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Macro F1	Macro P	Macro R	Subj F1	Subj P	Subj R	Accuracy
No log	1.0	46	0.6658	0.6925	0.7258	0.7124	0.7160	0.6080	0.8705	0.6943
No log	2.0	92	0.5538	0.7673	0.7748	0.7646	0.7280	0.7787	0.6835	0.7739
No log	3.0	138	0.5300	0.7353	0.7690	0.7327	0.6695	0.8144	0.5683	0.7516
No log	4.0	184	0.5090	0.7680	0.7833	0.7645	0.7222	0.8053	0.6547	0.7771
No log	5.0	230	0.5065	0.7728	0.7835	0.7696	0.7315	0.7966	0.6763	0.7803
No log	6.0	276	0.5111	0.7869	0.7949	0.7839	0.7510	0.8033	0.7050	0.7930

Framework versions

• Transformers 4.50.0
• Pytorch 2.5.1+cu121
• Datasets 3.3.1
• Tokenizers 0.21.0