albert-base-v2-finetuned-squad
This model is a fine-tuned version of albert-base-v2 on the squad_v2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.9492
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8695 | 1.0 | 8248 | 0.8813 |
| 0.6333 | 2.0 | 16496 | 0.8042 |
| 0.4372 | 3.0 | 24744 | 0.9492 |
Framework versions
- Transformers 4.12.3
- Pytorch 1.7.1
- Datasets 1.15.1
- Tokenizers 0.10.3
- Downloads last month
- 62
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.