---
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
model-index:
- name: deberta-v3-small-kaggle-mlm
  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. -->

# deberta-v3-small-kaggle-mlm

This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6169

## 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: 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 3.0931        | 1.0   | 6848   | 2.8467          |
| 2.6186        | 2.0   | 13696  | 2.4089          |
| 2.3498        | 3.0   | 20544  | 2.2224          |
| 2.2399        | 4.0   | 27392  | 2.1105          |
| 2.1226        | 5.0   | 34240  | 2.0204          |
| 2.0768        | 6.0   | 41088  | 1.9402          |
| 2.0251        | 7.0   | 47936  | 1.8767          |
| 1.9587        | 8.0   | 54784  | 1.8527          |
| 1.9209        | 9.0   | 61632  | 1.8108          |
| 1.8829        | 10.0  | 68480  | 1.8113          |
| 1.8454        | 11.0  | 75328  | 1.7698          |
| 1.8077        | 12.0  | 82176  | 1.7504          |
| 1.7991        | 13.0  | 89024  | 1.7390          |
| 1.7896        | 14.0  | 95872  | 1.7138          |
| 1.7608        | 15.0  | 102720 | 1.6847          |
| 1.7636        | 16.0  | 109568 | 1.6863          |
| 1.7416        | 17.0  | 116416 | 1.6816          |
| 1.7363        | 18.0  | 123264 | 1.6651          |
| 1.7013        | 19.0  | 130112 | 1.6465          |
| 1.6828        | 20.0  | 136960 | 1.6528          |
| 1.6889        | 21.0  | 143808 | 1.6406          |
| 1.6882        | 22.0  | 150656 | 1.6358          |
| 1.6742        | 23.0  | 157504 | 1.6338          |
| 1.6657        | 24.0  | 164352 | 1.6062          |
| 1.6685        | 25.0  | 171200 | 1.6086          |
| 1.6701        | 26.0  | 178048 | 1.6256          |
| 1.6755        | 27.0  | 184896 | 1.6186          |
| 1.6505        | 28.0  | 191744 | 1.6013          |
| 1.6573        | 29.0  | 198592 | 1.6108          |
| 1.6497        | 30.0  | 205440 | 1.6009          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1