metadata
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: fine-tuned-QAS-Squad_2-with-roberta-large
results: []
fine-tuned-QAS-Squad_2-with-roberta-large
This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7481
- Exact Match: 71.7912
- F1: 85.1553
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 |
|---|---|---|---|---|---|
| 0.957 | 0.5 | 463 | 0.8279 | 64.8987 | 79.7543 |
| 0.7977 | 1.0 | 926 | 0.7340 | 68.8325 | 82.9258 |
| 0.6992 | 1.5 | 1389 | 0.7095 | 69.8327 | 83.3647 |
| 0.6556 | 2.0 | 1852 | 0.6849 | 70.2278 | 84.0408 |
| 0.5743 | 2.5 | 2315 | 0.6992 | 70.4715 | 84.3736 |
| 0.574 | 3.0 | 2778 | 0.6917 | 70.9507 | 85.1835 |
| 0.4734 | 3.5 | 3241 | 0.7291 | 70.8330 | 84.8717 |
| 0.4733 | 4.0 | 3704 | 0.6828 | 71.6567 | 85.1160 |
| 0.4171 | 4.5 | 4167 | 0.7481 | 71.7912 | 85.1553 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2