x-sensitive-deberta-lora
This model is a fine-tuned version of faketut/x-sensitive-deberta-binary on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4249
- Accuracy: 0.8335
- F1: 0.8427
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 313 | 0.3246 | 0.882 | 0.8618 |
| 0.2531 | 2.0 | 626 | 0.3311 | 0.878 | 0.8601 |
| 0.2531 | 3.0 | 939 | 0.3298 | 0.88 | 0.8614 |
Framework versions
- PEFT 0.17.1
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.3.0
- Tokenizers 0.22.1
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Model tree for faketut/x-sensitive-deberta-lora
Base model
microsoft/deberta-v3-base Finetuned
faketut/x-sensitive-deberta-binary