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

# microsoft-deberta-v3-large

This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5698
- Pearson R: 0.8241
- Spearman R: 0.8276

## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 64
- 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Pearson R | Spearman R |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:----------:|
| 0.6835        | 1.0   | 719  | 0.6543          | 0.5224    | 0.5221     |
| 0.6489        | 2.0   | 1438 | 0.6053          | 0.7743    | 0.7848     |
| 0.6408        | 3.0   | 2157 | 0.6005          | 0.7826    | 0.7938     |
| 0.6288        | 4.0   | 2876 | 0.5970          | 0.7778    | 0.7792     |
| 0.6138        | 5.0   | 3595 | 0.6643          | 0.7622    | 0.7814     |
| 0.6044        | 6.0   | 4314 | 0.6048          | 0.8059    | 0.8135     |
| 0.597         | 7.0   | 5033 | 0.5865          | 0.8243    | 0.8307     |
| 0.5946        | 8.0   | 5752 | 0.5702          | 0.8170    | 0.8236     |
| 0.5915        | 9.0   | 6471 | 0.5738          | 0.8211    | 0.8242     |
| 0.5891        | 10.0  | 7190 | 0.5698          | 0.8241    | 0.8276     |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0