---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: FAQs_DistillBERT
  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. -->

# FAQs_DistillBERT

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1075

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 194  | 0.1131          |
| No log        | 2.0   | 388  | 0.1129          |
| 0.0986        | 3.0   | 582  | 0.1211          |
| 0.0986        | 4.0   | 776  | 0.1023          |
| 0.0986        | 5.0   | 970  | 0.1023          |
| 0.0589        | 6.0   | 1164 | 0.1051          |
| 0.0589        | 7.0   | 1358 | 0.1044          |
| 0.0327        | 8.0   | 1552 | 0.1100          |
| 0.0327        | 9.0   | 1746 | 0.0981          |
| 0.0327        | 10.0  | 1940 | 0.1029          |
| 0.0209        | 11.0  | 2134 | 0.0960          |
| 0.0209        | 12.0  | 2328 | 0.0969          |
| 0.0126        | 13.0  | 2522 | 0.1022          |
| 0.0126        | 14.0  | 2716 | 0.0985          |
| 0.0126        | 15.0  | 2910 | 0.1139          |
| 0.0095        | 16.0  | 3104 | 0.1139          |
| 0.0095        | 17.0  | 3298 | 0.1025          |
| 0.0095        | 18.0  | 3492 | 0.0986          |
| 0.0062        | 19.0  | 3686 | 0.0962          |
| 0.0062        | 20.0  | 3880 | 0.0949          |
| 0.0029        | 21.0  | 4074 | 0.1059          |
| 0.0029        | 22.0  | 4268 | 0.1098          |
| 0.0029        | 23.0  | 4462 | 0.1088          |
| 0.0035        | 24.0  | 4656 | 0.1047          |
| 0.0035        | 25.0  | 4850 | 0.1138          |
| 0.003         | 26.0  | 5044 | 0.1101          |
| 0.003         | 27.0  | 5238 | 0.1064          |
| 0.003         | 28.0  | 5432 | 0.0978          |
| 0.0028        | 29.0  | 5626 | 0.1100          |
| 0.0028        | 30.0  | 5820 | 0.1007          |
| 0.0027        | 31.0  | 6014 | 0.1038          |
| 0.0027        | 32.0  | 6208 | 0.0982          |
| 0.0027        | 33.0  | 6402 | 0.1057          |
| 0.0044        | 34.0  | 6596 | 0.1100          |
| 0.0044        | 35.0  | 6790 | 0.0932          |
| 0.0044        | 36.0  | 6984 | 0.0961          |
| 0.0027        | 37.0  | 7178 | 0.0973          |
| 0.0027        | 38.0  | 7372 | 0.0968          |
| 0.0018        | 39.0  | 7566 | 0.0942          |
| 0.0018        | 40.0  | 7760 | 0.1006          |
| 0.0018        | 41.0  | 7954 | 0.1028          |
| 0.0025        | 42.0  | 8148 | 0.1023          |
| 0.0025        | 43.0  | 8342 | 0.1006          |
| 0.0018        | 44.0  | 8536 | 0.1051          |
| 0.0018        | 45.0  | 8730 | 0.1056          |
| 0.0018        | 46.0  | 8924 | 0.1072          |
| 0.0019        | 47.0  | 9118 | 0.1075          |
| 0.0019        | 48.0  | 9312 | 0.1074          |
| 0.0017        | 49.0  | 9506 | 0.1074          |
| 0.0017        | 50.0  | 9700 | 0.1075          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2