metadata
library_name: transformers
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: nli-subgroups-target-abroad
results: []
nli-subgroups-target-abroad
This model is a fine-tuned version of microsoft/mdeberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3895
- Accuracy: 0.9270
- Precision Binary: 0.5491
- Recall Binary: 0.6333
- F1 Binary: 0.5882
- Precision Micro: 0.9270
- Recall Micro: 0.9270
- F1 Micro: 0.9270
- Pr Auc: 0.5737
- Cohen Kappa: 0.5484
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: 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
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Binary | Recall Binary | F1 Binary | Precision Micro | Recall Micro | F1 Micro | Pr Auc | Cohen Kappa |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 456 | 1.0509 | 0.9237 | 0.5307 | 0.6333 | 0.5775 | 0.9237 | 0.9237 | 0.9237 | 0.5397 | 0.5359 |
| 1.1638 | 2.0 | 912 | 0.7448 | 0.9303 | 0.5782 | 0.5667 | 0.5724 | 0.9303 | 0.9303 | 0.9303 | 0.5361 | 0.5345 |
| 0.9414 | 3.0 | 1368 | 1.3895 | 0.9270 | 0.5491 | 0.6333 | 0.5882 | 0.9270 | 0.9270 | 0.9270 | 0.5737 | 0.5484 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1