---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
model-index:
- name: bold-cod-455
  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. -->

# bold-cod-455

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: 0.1686
- Hamming Loss: 0.0605
- Zero One Loss: 0.38
- Jaccard Score: 0.3247
- Hamming Loss Optimised: 0.0579
- Hamming Loss Threshold: 0.5913
- Zero One Loss Optimised: 0.3862
- Zero One Loss Threshold: 0.4581
- Jaccard Score Optimised: 0.3111
- Jaccard Score Threshold: 0.3022

## 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: 2.6795250522175907e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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: 9

### 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   | 100  | 0.2399          | 0.0751       | 0.6375        | 0.6196        | 0.0736                 | 0.4031                 | 0.5413                  | 0.2884                  | 0.4770                  | 0.2690                  |
| No log        | 2.0   | 200  | 0.1861          | 0.062        | 0.4600        | 0.4166        | 0.0617                 | 0.6009                 | 0.4487                  | 0.4640                  | 0.3375                  | 0.2916                  |
| No log        | 3.0   | 300  | 0.1692          | 0.0583       | 0.4525        | 0.4103        | 0.0579                 | 0.5425                 | 0.4087                  | 0.4147                  | 0.3241                  | 0.2491                  |
| No log        | 4.0   | 400  | 0.1648          | 0.0589       | 0.4237        | 0.3791        | 0.0576                 | 0.5207                 | 0.4                     | 0.4601                  | 0.3181                  | 0.2985                  |
| 0.2003        | 5.0   | 500  | 0.1648          | 0.0594       | 0.4087        | 0.3603        | 0.0574                 | 0.5612                 | 0.4113                  | 0.4029                  | 0.3139                  | 0.3039                  |
| 0.2003        | 6.0   | 600  | 0.1707          | 0.0617       | 0.4025        | 0.3389        | 0.0587                 | 0.6338                 | 0.3988                  | 0.5041                  | 0.3148                  | 0.2846                  |
| 0.2003        | 7.0   | 700  | 0.1701          | 0.0606       | 0.3888        | 0.3359        | 0.0586                 | 0.6001                 | 0.39                    | 0.4468                  | 0.3147                  | 0.2914                  |
| 0.2003        | 8.0   | 800  | 0.1690          | 0.0614       | 0.385         | 0.3303        | 0.0584                 | 0.6970                 | 0.3838                  | 0.5334                  | 0.3155                  | 0.2859                  |
| 0.2003        | 9.0   | 900  | 0.1686          | 0.0605       | 0.38          | 0.3247        | 0.0579                 | 0.5913                 | 0.3862                  | 0.4581                  | 0.3111                  | 0.3022                  |


### Framework versions

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