| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: saracandu/stldec_arch |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: stldec_arch |
| | 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. --> |
| |
|
| | # stldec_arch |
| | |
| | This model is a fine-tuned version of [saracandu/stldec_arch](https://huggingface.co/saracandu/stldec_arch) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.8738 |
| | |
| | ## 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: 0.0001 |
| | - train_batch_size: 128 |
| | - eval_batch_size: 128 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 512 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | No log | 0 | 0 | 3.8917 | |
| | | 2.7225 | 0.6483 | 100 | 2.6803 | |
| | | 1.6189 | 1.2917 | 200 | 1.5324 | |
| | | 0.9914 | 1.9400 | 300 | 0.9894 | |
| | | 0.8278 | 2.5835 | 400 | 0.9311 | |
| | | 0.7646 | 3.2269 | 500 | 0.9649 | |
| | | 0.7273 | 3.8752 | 600 | 0.9046 | |
| | | 0.706 | 4.5186 | 700 | 0.8855 | |
| | | 0.6927 | 5.1621 | 800 | 0.8959 | |
| | | 0.6813 | 5.8104 | 900 | 0.8868 | |
| | | 0.6719 | 6.4538 | 1000 | 0.8772 | |
| | | 0.6683 | 7.0972 | 1100 | 0.8766 | |
| | | 0.6584 | 7.7455 | 1200 | 0.8761 | |
| | | 0.6592 | 8.3890 | 1300 | 0.8714 | |
| | | 0.6567 | 9.0324 | 1400 | 0.8729 | |
| | | 0.6512 | 9.6807 | 1500 | 0.8738 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.57.3 |
| | - Pytorch 2.9.1+cu128 |
| | - Datasets 4.4.2 |
| | - Tokenizers 0.22.1 |
| | |
