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---
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
model-index:
- name: deberta-v3-large-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-large-kaggle-mlm
This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co./microsoft/deberta-v3-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3182
## 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 |
|:-------------:|:-----:|:------:|:---------------:|
| 3.1114 | 1.0 | 6848 | 2.6616 |
| 2.2122 | 2.0 | 13696 | 1.9734 |
| 2.0848 | 3.0 | 20544 | 1.9930 |
| 1.8056 | 4.0 | 27392 | 1.7167 |
| 1.7003 | 5.0 | 34240 | 1.8419 |
| 1.6414 | 6.0 | 41088 | 1.5828 |
| 1.583 | 7.0 | 47936 | 1.5298 |
| 1.5245 | 8.0 | 54784 | 1.4964 |
| 1.491 | 9.0 | 61632 | 1.4671 |
| 1.4662 | 10.0 | 68480 | 1.4805 |
| 1.426 | 11.0 | 75328 | 1.4506 |
| 1.3924 | 12.0 | 82176 | 1.4272 |
| 1.3797 | 13.0 | 89024 | 1.4092 |
| 1.3713 | 14.0 | 95872 | 1.3947 |
| 1.3444 | 15.0 | 102720 | 1.3765 |
| 1.3414 | 16.0 | 109568 | 1.3636 |
| 1.3256 | 17.0 | 116416 | 1.3700 |
| 1.3084 | 18.0 | 123264 | 1.3607 |
| 1.2925 | 19.0 | 130112 | 1.3428 |
| 1.2615 | 20.0 | 136960 | 1.3483 |
| 1.2733 | 21.0 | 143808 | 1.3440 |
| 1.2809 | 22.0 | 150656 | 1.3314 |
| 1.2576 | 23.0 | 157504 | 1.3388 |
| 1.2606 | 24.0 | 164352 | 1.3126 |
| 1.2608 | 25.0 | 171200 | 1.3211 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
|