unique-gnu-764
This model is a fine-tuned version of 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
- Downloads last month
- 104
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for ElMad/unique-gnu-764
Base model
FacebookAI/roberta-base