multi-label_classification
This model is a fine-tuned version of kz-transformers/kaz-roberta-conversational on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3160
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.1891 | 1.0 | 6750 | 0.3160 |
| 0.3396 | 2.0 | 13500 | 0.3678 |
| 0.0354 | 3.0 | 20250 | 0.4509 |
| 0.0762 | 4.0 | 27000 | 0.5246 |
| 0.0003 | 5.0 | 33750 | 0.6247 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for Akzhannn/multi-label_classification
Base model
kz-transformers/kaz-roberta-conversational