---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
model-index:
- name: melodic-bee-938
  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. -->

# melodic-bee-938

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: 0.3387
- Hamming Loss: 0.1123
- Zero One Loss: 1.0
- Jaccard Score: 1.0
- Hamming Loss Optimised: 0.1123
- Hamming Loss Threshold: 0.9000
- Zero One Loss Optimised: 1.0
- Zero One Loss Threshold: 0.9000
- Jaccard Score Optimised: 1.0
- Jaccard Score Threshold: 0.9000

## 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: 0.0011128424281972827
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:-------------:|:-------------:|:----------------------:|:----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|
| 0.3511        | 1.0   | 100  | 0.3435          | 0.1123       | 1.0           | 1.0           | 0.1123                 | 0.9000                 | 1.0                     | 0.9000                  | 1.0                     | 0.9000                  |
| 0.3408        | 2.0   | 200  | 0.3418          | 0.1123       | 1.0           | 1.0           | 0.1123                 | 0.9000                 | 1.0                     | 0.9000                  | 1.0                     | 0.9000                  |
| 0.3393        | 3.0   | 300  | 0.3440          | 0.1123       | 1.0           | 1.0           | 0.1123                 | 0.9000                 | 1.0                     | 0.9000                  | 1.0                     | 0.9000                  |
| 0.3377        | 4.0   | 400  | 0.3395          | 0.1123       | 1.0           | 1.0           | 0.1123                 | 0.9000                 | 1.0                     | 0.9000                  | 1.0                     | 0.9000                  |
| 0.3363        | 5.0   | 500  | 0.3408          | 0.1123       | 1.0           | 1.0           | 0.1123                 | 0.9000                 | 1.0                     | 0.9000                  | 1.0                     | 0.9000                  |
| 0.3362        | 6.0   | 600  | 0.3397          | 0.1123       | 1.0           | 1.0           | 0.1123                 | 0.9000                 | 1.0                     | 0.9000                  | 1.0                     | 0.9000                  |
| 0.3349        | 7.0   | 700  | 0.3420          | 0.1123       | 1.0           | 1.0           | 0.1123                 | 0.9000                 | 1.0                     | 0.9000                  | 1.0                     | 0.9000                  |
| 0.334         | 8.0   | 800  | 0.3397          | 0.1123       | 1.0           | 1.0           | 0.1123                 | 0.9000                 | 1.0                     | 0.9000                  | 1.0                     | 0.9000                  |
| 0.3337        | 9.0   | 900  | 0.3387          | 0.1123       | 1.0           | 1.0           | 0.1123                 | 0.9000                 | 1.0                     | 0.9000                  | 1.0                     | 0.9000                  |


### Framework versions

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