---
library_name: peft
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
model-index:
- name: bustling-sheep-989
  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. -->

# bustling-sheep-989

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: 0.7152
- Hamming Loss: 0.4695
- Zero One Loss: 1.0
- Jaccard Score: 0.8591
- Hamming Loss Optimised: 0.1123
- Hamming Loss Threshold: 0.6789
- Zero One Loss Optimised: 0.8662
- Zero One Loss Threshold: 0.5944
- Jaccard Score Optimised: 0.8445
- Jaccard Score Threshold: 0.5669

## 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: 3.2020206916802435e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 2024
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.8180574670796091,0.9816119412827323) and epsilon=1e-07 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Hamming Loss | Zero One Loss | Jaccard Score | Hamming Loss Optimised | Hamming Loss Threshold | Zero One Loss Optimised | Zero One Loss Threshold | Jaccard Score Optimised | Jaccard Score Threshold |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:-------------:|:-------------:|:----------------------:|:----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|
| No log        | 1.0   | 400  | 0.7155          | 0.4695       | 1.0           | 0.8591        | 0.1123                 | 0.6789                 | 0.8662                  | 0.5944                  | 0.8445                  | 0.5669                  |
| 0.717         | 2.0   | 800  | 0.7152          | 0.4695       | 1.0           | 0.8591        | 0.1123                 | 0.6789                 | 0.8662                  | 0.5944                  | 0.8445                  | 0.5669                  |


### Framework versions

- PEFT 0.13.2
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0