---
library_name: peft
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
model-index:
- name: zealous-fowl-600
  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. -->

# zealous-fowl-600

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: 0.6860
- Hamming Loss: 0.369
- Zero One Loss: 1.0
- Jaccard Score: 0.9302
- Hamming Loss Optimised: 0.1123
- Hamming Loss Threshold: 0.6927
- Zero One Loss Optimised: 0.9613
- Zero One Loss Threshold: 0.5584
- Jaccard Score Optimised: 0.8878
- Jaccard Score Threshold: 0.2889

## 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: 1.3368760240891046e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 2024
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9127257778280685,0.9582541835167471) and epsilon=1e-07 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4

### 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  | 0.6867          | 0.3756       | 1.0           | 0.9288        | 0.1123                 | 0.6927                 | 0.9613                  | 0.5584                  | 0.8878                  | 0.2889                  |
| 0.6886        | 2.0   | 800  | 0.6863          | 0.3708       | 1.0           | 0.9300        | 0.1123                 | 0.6927                 | 0.9613                  | 0.5584                  | 0.8878                  | 0.2889                  |
| 0.6885        | 3.0   | 1200 | 0.6861          | 0.3693       | 1.0           | 0.9305        | 0.1123                 | 0.6927                 | 0.9613                  | 0.5584                  | 0.8878                  | 0.2889                  |
| 0.6876        | 4.0   | 1600 | 0.6860          | 0.369        | 1.0           | 0.9302        | 0.1123                 | 0.6927                 | 0.9613                  | 0.5584                  | 0.8878                  | 0.2889                  |


### Framework versions

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