metadata
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
model-index:
- name: deberta-v3-base_smcalflow-classifier
results: []
deberta-v3-base_smcalflow-classifier
This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0679
- F1 Micro: 0.7989
- F1 Macro: 0.1141
- Exact Match: 0.0625
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: 32
- eval_batch_size: 64
- 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
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Exact Match |
|---|---|---|---|---|---|---|
| 0.0820 | 1.0 | 656 | 0.1066 | 0.5700 | 0.0268 | 0.0 |
| 0.0632 | 2.0 | 1312 | 0.0815 | 0.7238 | 0.0548 | 0.0 |
| 0.0491 | 3.0 | 1968 | 0.0724 | 0.7640 | 0.0881 | 0.0111 |
| 0.0417 | 4.0 | 2624 | 0.0686 | 0.7921 | 0.1111 | 0.0486 |
| 0.0387 | 5.0 | 3280 | 0.0679 | 0.7989 | 0.1141 | 0.0625 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2