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---
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
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