---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- policies-named-insured
model-index:
- name: bert-large-uncased-whole-word-masking-finetuned-policy-named-insured
  results: []
---

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# bert-large-uncased-whole-word-masking-finetuned-policy-named-insured

This model is a fine-tuned version of [bert-large-uncased-whole-word-masking-finetuned-squad](https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad) on the policies-named-insured dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0264

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 478  | 0.0402          |
| 0.0557        | 2.0   | 956  | 0.0326          |
| 0.0106        | 3.0   | 1434 | 0.0264          |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.8.0
- Tokenizers 0.13.2