metadata
license: apache-2.0
base_model: google-bert/bert-base-cased
tags:
- question-answering
- nlp
- generated_from_trainer
metrics:
- f1
model-index:
- name: bert-base-cased-qa-mash-covid
results: []
bert-base-cased-qa-mash-covid
This model is a fine-tuned version of google-bert/bert-base-cased on the mashqa_covid_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.4945
- Exact Match: 0.0
- F1: 0.0
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 | Exact Match | F1 |
|---|---|---|---|---|---|
| 0.9127 | 1.0 | 2820 | 0.5115 | 0.0 | 0.0 |
| 0.7236 | 2.0 | 5640 | 0.4775 | 0.0 | 0.0 |
| 0.5733 | 3.0 | 8460 | 0.4945 | 0.0 | 0.0 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2