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---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
model-index:
- name: deberta-v3-base-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-base-kaggle-mlm
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5600
## 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: 25
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 3.1466 | 1.0 | 6848 | 2.9173 |
| 2.6316 | 2.0 | 13696 | 2.4139 |
| 2.3281 | 3.0 | 20544 | 2.2020 |
| 2.2122 | 4.0 | 27392 | 2.0776 |
| 2.0794 | 5.0 | 34240 | 1.9780 |
| 2.0299 | 6.0 | 41088 | 1.8861 |
| 1.9629 | 7.0 | 47936 | 1.8213 |
| 1.9001 | 8.0 | 54784 | 1.7946 |
| 1.8508 | 9.0 | 61632 | 1.7551 |
| 1.8157 | 10.0 | 68480 | 1.7485 |
| 1.7815 | 11.0 | 75328 | 1.7100 |
| 1.7423 | 12.0 | 82176 | 1.6970 |
| 1.7318 | 13.0 | 89024 | 1.6813 |
| 1.7173 | 14.0 | 95872 | 1.6493 |
| 1.6902 | 15.0 | 102720 | 1.6243 |
| 1.7002 | 16.0 | 109568 | 1.6313 |
| 1.6714 | 17.0 | 116416 | 1.6181 |
| 1.6605 | 18.0 | 123264 | 1.6026 |
| 1.6331 | 19.0 | 130112 | 1.5825 |
| 1.6143 | 20.0 | 136960 | 1.5903 |
| 1.6136 | 21.0 | 143808 | 1.5812 |
| 1.6151 | 22.0 | 150656 | 1.5708 |
| 1.6122 | 23.0 | 157504 | 1.5806 |
| 1.6025 | 24.0 | 164352 | 1.5492 |
| 1.614 | 25.0 | 171200 | 1.5555 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
|