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---
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
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