---
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
model-index:
- name: experiment_lr_20241214_130720
  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. -->

# experiment_lr_20241214_130720

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0103
- Exact Match Accuracy: 0.8830

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Exact Match Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------------------:|
| 0.014         | 1.0   | 4594  | 0.0125          | 0.6134               |
| 0.0023        | 2.0   | 9188  | 0.0072          | 0.8473               |
| 0.0009        | 3.0   | 13782 | 0.0078          | 0.8711               |
| 0.0006        | 4.0   | 18376 | 0.0085          | 0.8711               |
| 0.0003        | 5.0   | 22970 | 0.0094          | 0.8685               |
| 0.0002        | 6.0   | 27564 | 0.0096          | 0.8771               |
| 0.0002        | 7.0   | 32158 | 0.0095          | 0.8824               |
| 0.0001        | 8.0   | 36752 | 0.0111          | 0.8744               |
| 0.0001        | 9.0   | 41346 | 0.0103          | 0.8830               |
| 0.0001        | 10.0  | 45940 | 0.0100          | 0.8824               |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0