adaptation_diacritized

This model is a fine-tuned version of lazymonster/15k-combined-diacritized-scratch on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.0240
• Accuracy: 0.6734
• F1 Macro: 0.6510
• Composite Score: 0.6510

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: 32
• eval_batch_size: 32
• 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
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 20
• mixed_precision_training: Native AMP
• label_smoothing_factor: 0.1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro	Composite Score
No log	1.0	267	0.9467	0.6662	0.6397	0.6397
0.5963	2.0	534	0.9685	0.6504	0.6373	0.6373
0.5963	3.0	801	0.9401	0.6686	0.6457	0.6457
0.5689	4.0	1068	0.9578	0.6671	0.6433	0.6433
0.5689	5.0	1335	0.9699	0.6681	0.6452	0.6452
0.5488	6.0	1602	0.9692	0.6758	0.6484	0.6484
0.5488	7.0	1869	0.9762	0.6715	0.6513	0.6513
0.5263	8.0	2136	0.9864	0.6786	0.6530	0.6530
0.5263	9.0	2403	0.9853	0.6777	0.6523	0.6523
0.5072	10.0	2670	0.9843	0.6844	0.6573	0.6573
0.5072	11.0	2937	1.0037	0.6782	0.6553	0.6553
0.4946	12.0	3204	0.9960	0.6767	0.6548	0.6548
0.4946	13.0	3471	1.0123	0.6810	0.6572	0.6572
0.488	14.0	3738	1.0240	0.6734	0.6510	0.6510

Framework versions

• Transformers 4.53.3
• Pytorch 2.6.0+cu124
• Datasets 4.4.1
• Tokenizers 0.21.2