pytorch distilbert question-answering dataset:natural_questions transformers generated_from_trainer license:apache-2.0 model-index autotrain_compatible
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- natural_questions
model-index:
- name: distilbert-base-uncased-finetuned-natural-questions
  results: []
---

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# distilbert-base-uncased-finetuned-natural-questions

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the natural_questions dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6267

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step   | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 2.0532        | 1.0   | 5104   | 0.2393          |
| 1.8912        | 2.0   | 10208  | 0.2284          |
| 1.7854        | 3.0   | 15312  | 0.2357          |
| 1.6856        | 4.0   | 20416  | 0.2487          |
| 1.5918        | 5.0   | 25520  | 0.2743          |
| 1.5067        | 6.0   | 30624  | 0.2586          |
| 1.4323        | 7.0   | 35728  | 0.2763          |
| 1.365         | 8.0   | 40832  | 0.2753          |
| 1.3162        | 9.0   | 45936  | 0.3200          |
| 1.281         | 10.0  | 51040  | 0.3127          |
| 1.308         | 11.0  | 57104  | 0.2947          |
| 1.241         | 12.0  | 62208  | 0.2941          |
| 1.1391        | 13.0  | 67312  | 0.3103          |
| 1.0334        | 14.0  | 72416  | 0.3694          |
| 0.9538        | 15.0  | 77520  | 0.3658          |
| 0.8749        | 16.0  | 82624  | 0.4009          |
| 0.8154        | 17.0  | 87728  | 0.3672          |
| 0.7533        | 18.0  | 92832  | 0.3675          |
| 0.7079        | 19.0  | 97936  | 0.4611          |
| 0.6658        | 20.0  | 103040 | 0.4222          |
| 0.595         | 21.0  | 108144 | 0.4095          |
| 0.5765        | 22.0  | 113248 | 0.4400          |
| 0.5259        | 23.0  | 118352 | 0.5109          |
| 0.4804        | 24.0  | 123456 | 0.4711          |
| 0.4389        | 25.0  | 128560 | 0.5072          |
| 0.4034        | 26.0  | 133664 | 0.5363          |
| 0.374         | 27.0  | 138768 | 0.5460          |
| 0.3434        | 28.0  | 143872 | 0.5627          |
| 0.3181        | 29.0  | 148976 | 0.5657          |
| 0.2971        | 30.0  | 154080 | 0.5819          |
| 0.275         | 31.0  | 159184 | 0.5649          |
| 0.2564        | 32.0  | 164288 | 0.6087          |
| 0.2431        | 33.0  | 169392 | 0.6137          |
| 0.2289        | 34.0  | 174496 | 0.6123          |
| 0.2151        | 35.0  | 179600 | 0.5979          |
| 0.2041        | 36.0  | 184704 | 0.6196          |
| 0.1922        | 37.0  | 189808 | 0.6191          |
| 0.1852        | 38.0  | 194912 | 0.6313          |
| 0.1718        | 39.0  | 200016 | 0.6234          |
| 0.1718        | 39.81 | 204160 | 0.6267          |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0
- Datasets 1.18.4
- Tokenizers 0.11.6
