lilt_robeczech_lr2e-05_bs4_train287

This model is a fine-tuned version of xkaska02/lilt-robeczech-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.4432
• Precision: 0.7229
• Recall: 0.7107
• F1: 0.7167
• Accuracy: 0.8486

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: 8
• eval_batch_size: 8
• 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: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	144	1.5198	1.0	0.0142	0.0281	0.5419
No log	2.0	288	1.0972	0.6422	0.2710	0.3811	0.6197
No log	3.0	432	1.0029	0.5608	0.4077	0.4722	0.6317
1.2975	4.0	576	0.6919	0.6922	0.5521	0.6143	0.7649
1.2975	5.0	720	0.5497	0.6687	0.6711	0.6699	0.8120
1.2975	6.0	864	0.5044	0.6935	0.6878	0.6907	0.8280
0.5204	7.0	1008	0.4790	0.6969	0.6873	0.6921	0.8318
0.5204	8.0	1152	0.4544	0.7147	0.7006	0.7076	0.8417
0.5204	9.0	1296	0.4698	0.7253	0.7006	0.7127	0.8455
0.5204	10.0	1440	0.4432	0.7229	0.7107	0.7167	0.8486
0.3239	11.0	1584	0.4521	0.7201	0.7011	0.7105	0.8469
0.3239	12.0	1728	0.4535	0.7323	0.7067	0.7193	0.8512
0.3239	13.0	1872	0.4511	0.7192	0.7031	0.7111	0.8486

Framework versions

• Transformers 4.51.3
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.21.1