valuable-squid-615
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: 0.1886
- Hamming Loss: 0.0605
- Zero One Loss: 0.4675
- Jaccard Score: 0.4289
- Hamming Loss Optimised: 0.0596
- Hamming Loss Threshold: 0.5113
- Zero One Loss Optimised: 0.4363
- Zero One Loss Threshold: 0.4054
- Jaccard Score Optimised: 0.3606
- Jaccard Score Threshold: 0.3059
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: 2.6795250522175907e-05
- 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: 3
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 | 0.2485 | 0.0774 | 0.6475 | 0.6308 | 0.0767 | 0.4029 | 0.5813 | 0.2602 | 0.5165 | 0.2275 |
| No log | 2.0 | 200 | 0.2005 | 0.0606 | 0.5 | 0.4601 | 0.0617 | 0.5541 | 0.4613 | 0.4187 | 0.3756 | 0.2803 |
| No log | 3.0 | 300 | 0.1886 | 0.0605 | 0.4675 | 0.4289 | 0.0596 | 0.5113 | 0.4363 | 0.4054 | 0.3606 | 0.3059 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0
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Model tree for ElMad/valuable-squid-615
Base model
FacebookAI/roberta-base