metadata
license: cc-by-4.0
base_model: deepset/deberta-v3-large-squad2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-large_vMCQ
results: []
deberta-large_vMCQ
This model is a fine-tuned version of deepset/deberta-v3-large-squad2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3480
- Accuracy: 0.9061
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5525 | 0.17 | 1000 | 0.4781 | 0.8777 |
| 0.4107 | 0.33 | 2000 | 0.3763 | 0.8924 |
| 0.3733 | 0.5 | 3000 | 0.3605 | 0.8967 |
| 0.39 | 0.67 | 4000 | 0.3378 | 0.9050 |
| 0.3674 | 0.83 | 5000 | 0.3407 | 0.9053 |
| 0.3507 | 1.0 | 6000 | 0.3480 | 0.9061 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1