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---
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- question-answering
- nlp
- generated_from_trainer
model-index:
- name: bert-qa-mash-covid
results: []
---
<!-- 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. -->
# bert-qa-mash-covid
This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co./google-bert/bert-base-uncased) on the mashqa_covid_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2296
## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 1.0 | 329 | 1.3881 |
| 1.6542 | 2.0 | 658 | 1.3044 |
| 1.6542 | 3.0 | 987 | 1.2296 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
|