|
--- |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- squad_v2 |
|
model-index: |
|
- name: roberta-finetuned-squad_v2 |
|
results: |
|
- task: |
|
type: question-answering |
|
name: Question Answering |
|
dataset: |
|
name: SQuAD v2 |
|
type: squad_v2 |
|
split: validation |
|
metrics: |
|
- type: exact |
|
value: 100.0 |
|
name: Exact |
|
- type: f1 |
|
value: 100.0 |
|
name: F1 |
|
- type: total |
|
value: 2 |
|
name: Total |
|
- type: HasAns_exact |
|
value: 100.0 |
|
name: Hasans_exact |
|
- type: HasAns_f1 |
|
value: 100.0 |
|
name: Hasans_f1 |
|
- type: HasAns_total |
|
value: 2 |
|
name: Hasans_total |
|
- type: best_exact |
|
value: 100.0 |
|
name: Best_exact |
|
- type: best_exact_thresh |
|
value: 0.9603068232536316 |
|
name: Best_exact_thresh |
|
- type: best_f1 |
|
value: 100.0 |
|
name: Best_f1 |
|
- type: best_f1_thresh |
|
value: 0.9603068232536316 |
|
name: Best_f1_thresh |
|
- type: total_time_in_seconds |
|
value: 0.036892927000735654 |
|
name: Total_time_in_seconds |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# roberta-finetuned-squad_v2 |
|
|
|
This model was trained from scratch on the squad_v2 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.8582 |
|
|
|
## 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: 128 |
|
- eval_batch_size: 128 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 512 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 4 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 2.9129 | 0.2 | 100 | 1.4700 | |
|
| 1.4395 | 0.39 | 200 | 1.2407 | |
|
| 1.2356 | 0.59 | 300 | 1.0325 | |
|
| 1.1284 | 0.78 | 400 | 0.9750 | |
|
| 1.0821 | 0.98 | 500 | 0.9345 | |
|
| 0.9978 | 1.18 | 600 | 0.9893 | |
|
| 0.9697 | 1.37 | 700 | 0.9300 | |
|
| 0.9455 | 1.57 | 800 | 0.9351 | |
|
| 0.9322 | 1.76 | 900 | 0.9451 | |
|
| 0.9269 | 1.96 | 1000 | 0.9064 | |
|
| 0.9105 | 2.16 | 1100 | 0.8837 | |
|
| 0.8805 | 2.35 | 1200 | 0.8876 | |
|
| 0.8703 | 2.55 | 1300 | 0.9853 | |
|
| 0.8699 | 2.75 | 1400 | 0.9235 | |
|
| 0.8633 | 2.94 | 1500 | 0.8930 | |
|
| 0.828 | 3.14 | 1600 | 0.8582 | |
|
| 0.8284 | 3.33 | 1700 | 0.9203 | |
|
| 0.8076 | 3.53 | 1800 | 0.8866 | |
|
| 0.7805 | 3.73 | 1900 | 0.9099 | |
|
| 0.7974 | 3.92 | 2000 | 0.8746 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.1 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.14.1 |
|
|
