metadata
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-base-finetuned-mcqa
results: []
deberta-v3-base-finetuned-mcqa
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: 1.3869
- Accuracy: 0.262
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3888 | 1.0 | 563 | 1.3869 | 0.262 |
| 1.3881 | 2.0 | 1126 | 1.3875 | 0.262 |
| 1.3877 | 3.0 | 1689 | 1.3871 | 0.236 |
| 1.3877 | 4.0 | 2252 | 1.3871 | 0.262 |
| 1.3873 | 5.0 | 2815 | 1.3867 | 0.236 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3