---
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
model-index:
- name: bemused-trout-607
  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. -->

# bemused-trout-607

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1783
- Hamming Loss: 0.0643
- Zero One Loss: 0.4113
- Jaccard Score: 0.3643
- Hamming Loss Optimised: 0.0615
- Hamming Loss Threshold: 0.7239
- Zero One Loss Optimised: 0.4038
- Zero One Loss Threshold: 0.4731
- Jaccard Score Optimised: 0.3281
- Jaccard Score Threshold: 0.2446

## 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: 5.0943791435964314e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 2024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:-------------:|:-------------:|:----------------------:|:----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|
| 0.2941        | 1.0   | 400  | 0.2355          | 0.0934       | 0.7987        | 0.7963        | 0.0929                 | 0.6046                 | 0.6738                  | 0.2934                  | 0.5524                  | 0.2658                  |
| 0.2247        | 2.0   | 800  | 0.2132          | 0.0914       | 0.6188        | 0.5905        | 0.0906                 | 0.6229                 | 0.6262                  | 0.3893                  | 0.4890                  | 0.2889                  |
| 0.187         | 3.0   | 1200 | 0.1854          | 0.066        | 0.4712        | 0.4224        | 0.0653                 | 0.7034                 | 0.4325                  | 0.4451                  | 0.3701                  | 0.4026                  |
| 0.1495        | 4.0   | 1600 | 0.1783          | 0.0643       | 0.4113        | 0.3643        | 0.0615                 | 0.7239                 | 0.4038                  | 0.4731                  | 0.3281                  | 0.2446                  |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3