---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
model-index:
- name: unique-gnu-764
  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. -->

# unique-gnu-764

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1730
- Hamming Loss: 0.0606
- Zero One Loss: 0.485
- Jaccard Score: 0.4424
- Hamming Loss Optimised: 0.059
- Hamming Loss Threshold: 0.5979
- Zero One Loss Optimised: 0.4225
- Zero One Loss Threshold: 0.3775
- Jaccard Score Optimised: 0.3443
- Jaccard Score Threshold: 0.2391

## 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: 9.099061382218765e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 2024
- 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
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:-------------:|:-------------:|:----------------------:|:----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|
| 0.3041        | 1.0   | 800  | 0.2106          | 0.0741       | 0.6013        | 0.5782        | 0.0751                 | 0.6394                 | 0.495                   | 0.3884                  | 0.4128                  | 0.2790                  |
| 0.181         | 2.0   | 1600 | 0.1730          | 0.0606       | 0.485         | 0.4424        | 0.059                  | 0.5979                 | 0.4225                  | 0.3775                  | 0.3443                  | 0.2391                  |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0