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---
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 |