---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: finetuned-DSCS24-mitre-distilbert-base-uncased-fill-mask
  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. -->

# finetuned-DSCS24-mitre-distilbert-base-uncased-fill-mask

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9549

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.6456        | 1.0   | 65   | 2.3685          |
| 2.3833        | 2.0   | 130  | 2.2661          |
| 2.282         | 3.0   | 195  | 2.2728          |
| 2.1715        | 4.0   | 260  | 2.1675          |
| 2.1186        | 5.0   | 325  | 2.1354          |
| 2.0968        | 6.0   | 390  | 2.0318          |
| 2.0885        | 7.0   | 455  | 2.1233          |
| 2.0212        | 8.0   | 520  | 2.0152          |
| 1.9305        | 9.0   | 585  | 2.0134          |
| 1.9843        | 10.0  | 650  | 2.0334          |
| 1.9682        | 11.0  | 715  | 1.9611          |
| 1.9383        | 12.0  | 780  | 2.0051          |
| 1.9075        | 13.0  | 845  | 1.9790          |
| 1.9107        | 14.0  | 910  | 1.9532          |
| 1.9352        | 15.0  | 975  | 1.9677          |
| 1.9102        | 16.0  | 1040 | 1.9569          |
| 1.9065        | 17.0  | 1105 | 1.9143          |
| 1.8659        | 18.0  | 1170 | 1.9818          |
| 1.8807        | 19.0  | 1235 | 1.9321          |
| 1.9088        | 20.0  | 1300 | 1.9549          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1