128Bert

This model is a fine-tuned version of cointegrated/rubert-tiny2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.8346
• Accuracy: 0.7033

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: 128
• eval_batch_size: 128
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.1934	1.0	2074	1.1488	0.6027
1.0626	2.0	4148	1.0247	0.6459
0.9729	3.0	6222	0.9483	0.6658
0.908	4.0	8296	0.9041	0.6811
0.8684	5.0	10370	0.8771	0.6897
0.8348	6.0	12444	0.8593	0.6956
0.8055	7.0	14518	0.8507	0.6991
0.7924	8.0	16592	0.8410	0.7017
0.7857	9.0	18666	0.8349	0.7037
0.7732	10.0	20740	0.8346	0.7033

Framework versions

• Transformers 4.40.1
• Pytorch 2.2.1+cu121
• Datasets 2.19.0
• Tokenizers 0.19.1