---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: my_awesome_qa_model
  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. -->

# my_awesome_qa_model

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the squad dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5143

## 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: 5e-05
- train_batch_size: 40
- eval_batch_size: 40
- seed: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 100  | 4.7435          |
| No log        | 2.0   | 200  | 4.3343          |
| No log        | 3.0   | 300  | 4.0804          |
| No log        | 4.0   | 400  | 3.8983          |
| 4.3932        | 5.0   | 500  | 3.7642          |
| 4.3932        | 6.0   | 600  | 3.6649          |
| 4.3932        | 7.0   | 700  | 3.5978          |
| 4.3932        | 8.0   | 800  | 3.5499          |
| 4.3932        | 9.0   | 900  | 3.5216          |
| 3.7318        | 10.0  | 1000 | 3.5143          |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.13.3