---
tags:
- generated_from_trainer
datasets:
- squad_v2
model-index:
- name: bert-finetuned-uncased-squad_v2
  results:
  - task:
      type: question-answering
      name: Question Answering
    dataset:
      name: SQuAD v2
      type: squad_v2
      split: validation
    metrics:
    - type: exact
      value: 100.0
      name: Exact
    - type: f1
      value: 100.0
      name: F1
    - type: total
      value: 2
      name: Total
    - type: HasAns_exact
      value: 100.0
      name: Hasans_exact
    - type: HasAns_f1
      value: 100.0
      name: Hasans_f1
    - type: HasAns_total
      value: 2
      name: Hasans_total
    - type: best_exact
      value: 100.0
      name: Best_exact
    - type: best_exact_thresh
      value: 0.9558643102645874
      name: Best_exact_thresh
---

<!-- 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-finetuned-uncased-squad_v2

This model was trained from scratch on the squad_v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1459

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.2307        | 0.2   | 100  | 1.8959          |
| 1.9581        | 0.39  | 200  | 1.4856          |
| 1.6358        | 0.59  | 300  | 1.3948          |
| 1.4964        | 0.78  | 400  | 1.2934          |
| 1.4169        | 0.98  | 500  | 1.2605          |
| 1.327         | 1.18  | 600  | 1.2218          |
| 1.2763        | 1.37  | 700  | 1.2539          |
| 1.2755        | 1.57  | 800  | 1.2090          |
| 1.251         | 1.76  | 900  | 1.2041          |
| 1.229         | 1.96  | 1000 | 1.2159          |
| 1.1921        | 2.16  | 1100 | 1.1828          |
| 1.1926        | 2.35  | 1200 | 1.2120          |
| 1.1606        | 2.55  | 1300 | 1.1737          |
| 1.1486        | 2.75  | 1400 | 1.1469          |
| 1.1195        | 2.94  | 1500 | 1.1459          |
| 1.0883        | 3.14  | 1600 | 1.1570          |
| 1.0526        | 3.33  | 1700 | 1.1771          |
| 1.0611        | 3.53  | 1800 | 1.1740          |
| 1.0521        | 3.73  | 1900 | 1.1596          |
| 1.0476        | 3.92  | 2000 | 1.1538          |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1