---
tags:
- generated_from_trainer
datasets:
- squad_v2
model-index:
- name: distilbert-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: 0.7474104762077332
      name: Best_exact_thresh
    - type: best_f1
      value: 100.0
      name: Best_f1
    - type: best_f1_thresh
      value: 0.7474104762077332
      name: Best_f1_thresh
    - type: total_time_in_seconds
      value: 0.02269491500192089
      name: Total_time_in_seconds
    - type: samples_per_second
      value: 88.1254677460004
      name: Samples_per_second
    - type: latency_in_seconds
      value: 0.011347457500960445
      name: Latency_in_seconds
---

<!-- 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. -->

# distilbert-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: 1.3332

## 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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 3.6437        | 0.39  | 100  | 2.1780          |
| 2.1596        | 0.78  | 200  | 1.6557          |
| 1.8138        | 1.18  | 300  | 1.5683          |
| 1.6987        | 1.57  | 400  | 1.5076          |
| 1.6586        | 1.96  | 500  | 1.5350          |
| 1.5957        | 1.18  | 600  | 1.4431          |
| 1.5825        | 1.37  | 700  | 1.4955          |
| 1.5523        | 1.57  | 800  | 1.4444          |
| 1.5346        | 1.76  | 900  | 1.3930          |
| 1.5098        | 1.96  | 1000 | 1.4285          |
| 1.4632        | 2.16  | 1100 | 1.3630          |
| 1.4468        | 2.35  | 1200 | 1.3710          |
| 1.4343        | 2.55  | 1300 | 1.3422          |
| 1.4225        | 2.75  | 1400 | 1.3971          |
| 1.408         | 2.94  | 1500 | 1.4355          |
| 1.3609        | 3.14  | 1600 | 1.3332          |
| 1.3398        | 3.33  | 1700 | 1.3792          |
| 1.3224        | 3.53  | 1800 | 1.4172          |
| 1.3152        | 3.73  | 1900 | 1.3956          |
| 1.3141        | 3.92  | 2000 | 1.3748          |


### Framework versions

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