---
library_name: peft
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
model-index:
- name: dapper-ape-848
  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. -->

# dapper-ape-848

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: 0.5164
- Hamming Loss: 0.1123
- Zero One Loss: 1.0
- Jaccard Score: 1.0
- Hamming Loss Optimised: 0.1123
- Hamming Loss Threshold: 0.5944
- Zero One Loss Optimised: 0.8712
- Zero One Loss Threshold: 0.4290
- Jaccard Score Optimised: 0.8190
- Jaccard Score Threshold: 0.4039

## 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: 8.506034831608646e-06
- 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: 11

### 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  | 0.7056          | 0.567        | 1.0           | 0.8855        | 0.1123                 | 0.5944                 | 1.0                     | 0.9000                  | 0.8878                  | 0.2889                  |
| No log        | 2.0   | 200  | 0.7020          | 0.4813       | 1.0           | 0.8993        | 0.1123                 | 0.5944                 | 1.0                     | 0.9000                  | 0.8878                  | 0.2889                  |
| No log        | 3.0   | 300  | 0.6961          | 0.4363       | 1.0           | 0.9071        | 0.1123                 | 0.5944                 | 1.0                     | 0.9000                  | 0.8878                  | 0.2889                  |
| No log        | 4.0   | 400  | 0.6856          | 0.4355       | 1.0           | 0.907         | 0.1123                 | 0.5944                 | 1.0                     | 0.9000                  | 0.8878                  | 0.2889                  |
| 0.6963        | 5.0   | 500  | 0.6619          | 0.2924       | 0.9912        | 0.9281        | 0.1123                 | 0.5944                 | 1.0                     | 0.9000                  | 0.8878                  | 0.2889                  |
| 0.6963        | 6.0   | 600  | 0.6033          | 0.1124       | 1.0           | 1.0           | 0.1123                 | 0.5944                 | 1.0                     | 0.9000                  | 0.8540                  | 0.4530                  |
| 0.6963        | 7.0   | 700  | 0.5635          | 0.1123       | 1.0           | 1.0           | 0.1123                 | 0.5944                 | 1.0                     | 0.9000                  | 0.8212                  | 0.4305                  |
| 0.6963        | 8.0   | 800  | 0.5386          | 0.1123       | 1.0           | 1.0           | 0.1123                 | 0.5944                 | 1.0                     | 0.9000                  | 0.8135                  | 0.4232                  |
| 0.6963        | 9.0   | 900  | 0.5250          | 0.1123       | 1.0           | 1.0           | 0.1123                 | 0.5944                 | 0.895                   | 0.4370                  | 0.8192                  | 0.4047                  |
| 0.5852        | 10.0  | 1000 | 0.5184          | 0.1123       | 1.0           | 1.0           | 0.1123                 | 0.5944                 | 0.88                    | 0.4306                  | 0.8163                  | 0.4115                  |
| 0.5852        | 11.0  | 1100 | 0.5164          | 0.1123       | 1.0           | 1.0           | 0.1123                 | 0.5944                 | 0.8712                  | 0.4290                  | 0.8190                  | 0.4039                  |


### Framework versions

- PEFT 0.13.2
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0