---
license: apache-2.0
base_model: distilbert/distilbert-base-cased-distilled-squad
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-cased-distilled-squad-v2
  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. -->

# distilbert-base-cased-distilled-squad-v2

This model is a fine-tuned version of [distilbert/distilbert-base-cased-distilled-squad](https://huggingface.co/distilbert/distilbert-base-cased-distilled-squad) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9145

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.969         | 0.17  | 2500  | 0.8847          |
| 0.9411        | 0.34  | 5000  | 0.8974          |
| 0.9072        | 0.51  | 7500  | 0.8331          |
| 0.9098        | 0.68  | 10000 | 0.8146          |
| 0.866         | 0.85  | 12500 | 0.8371          |
| 0.6918        | 1.02  | 15000 | 0.8752          |
| 0.6142        | 1.19  | 17500 | 0.8580          |
| 0.6348        | 1.36  | 20000 | 0.8042          |
| 0.604         | 1.53  | 22500 | 0.8274          |
| 0.5953        | 1.7   | 25000 | 0.8006          |
| 0.6046        | 1.87  | 27500 | 0.8022          |
| 0.4395        | 2.04  | 30000 | 0.8887          |
| 0.4461        | 2.21  | 32500 | 0.9536          |
| 0.4254        | 2.38  | 35000 | 0.9380          |
| 0.4234        | 2.55  | 37500 | 0.9079          |
| 0.396         | 2.72  | 40000 | 0.9392          |
| 0.4161        | 2.89  | 42500 | 0.9145          |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1