---
license: apache-2.0
base_model: google-bert/bert-large-uncased-whole-word-masking-finetuned-squad
tags:
- generated_from_trainer
model-index:
- name: bert_large_uncased-QA1
  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_large_uncased-QA1

This model is a fine-tuned version of [google-bert/bert-large-uncased-whole-word-masking-finetuned-squad](https://huggingface.co/google-bert/bert-large-uncased-whole-word-masking-finetuned-squad) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6158

## 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
- lr_scheduler_warmup_steps: 100
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 9    | 3.4299          |
| No log        | 2.0   | 18   | 2.3637          |
| No log        | 3.0   | 27   | 1.3157          |
| No log        | 4.0   | 36   | 0.8384          |
| No log        | 5.0   | 45   | 0.6158          |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1