---
license: apache-2.0
base_model: distilbert-base-cased-distilled-squad
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-cased-distilled-squad-231123
  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-231123

This model is a fine-tuned version of [distilbert-base-cased-distilled-squad](https://huggingface.co/distilbert-base-cased-distilled-squad) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5287

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 116  | 1.9383          |
| No log        | 2.0   | 232  | 1.9901          |
| No log        | 3.0   | 348  | 2.0780          |
| No log        | 4.0   | 464  | 2.2501          |
| 1.4804        | 5.0   | 580  | 2.4190          |
| 1.4804        | 6.0   | 696  | 2.5925          |
| 1.4804        | 7.0   | 812  | 2.7649          |
| 1.4804        | 8.0   | 928  | 2.9029          |
| 0.5119        | 9.0   | 1044 | 3.0296          |
| 0.5119        | 10.0  | 1160 | 3.1669          |
| 0.5119        | 11.0  | 1276 | 3.3412          |
| 0.5119        | 12.0  | 1392 | 3.3165          |
| 0.2287        | 13.0  | 1508 | 3.4167          |
| 0.2287        | 14.0  | 1624 | 3.5039          |
| 0.2287        | 15.0  | 1740 | 3.5287          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0