kazroberta-finetuned-pos-halved-2nd
This model is a fine-tuned version of kz-transformers/kaz-roberta-conversational on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0223
- Accuracy: 0.9959
- Precision: 0.9912
- Recall: 0.9910
- F1: 0.9911
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: 5e-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_steps: 1000
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.089 | 1.0 | 1238 | 0.0591 | 0.9808 | 0.9573 | 0.9531 | 0.9549 |
| 0.0438 | 2.0 | 2476 | 0.0333 | 0.9897 | 0.9691 | 0.9752 | 0.9721 |
| 0.0165 | 3.0 | 3714 | 0.0242 | 0.9937 | 0.9807 | 0.9822 | 0.9814 |
| 0.0067 | 4.0 | 4952 | 0.0224 | 0.9952 | 0.9897 | 0.9888 | 0.9892 |
| 0.0028 | 5.0 | 6190 | 0.0223 | 0.9959 | 0.9912 | 0.9910 | 0.9911 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.7.0+cu126
- Datasets 3.5.1
- Tokenizers 0.21.1
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Model tree for quatatak/kazroberta-finetuned-pos-halved-2nd
Base model
kz-transformers/kaz-roberta-conversational