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library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: HybridModelScratch
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. -->
# HybridModelScratch
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 6.0191
- Accuracy: 0.1528
## 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: 64
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 1024
- total_eval_batch_size: 32
- 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: cosine
- lr_scheduler_warmup_steps: 150
- training_steps: 2000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 133.1257 | 0.05 | 100 | 7.7065 | 0.0876 |
| 107.0186 | 0.1 | 200 | 6.6099 | 0.1364 |
| 102.3462 | 0.15 | 300 | 6.3677 | 0.1448 |
| 99.0524 | 0.2 | 400 | 6.2145 | 0.1531 |
| 96.6031 | 0.25 | 500 | 6.1010 | 0.1584 |
| 95.9314 | 0.3 | 600 | 5.9869 | 0.1640 |
| 95.0101 | 0.35 | 700 | 5.8890 | 0.1683 |
| 94.2643 | 0.4 | 800 | 5.8284 | 0.1715 |
| 93.2266 | 0.45 | 900 | 5.7744 | 0.1746 |
| 92.0125 | 0.5 | 1000 | 5.7337 | 0.1763 |
| 95.8613 | 0.55 | 1100 | 6.0068 | 0.1554 |
| 98.1012 | 0.6 | 1200 | 6.1055 | 0.1491 |
| 97.152 | 0.65 | 1300 | 6.0546 | 0.1512 |
| 97.8734 | 0.7 | 1400 | 6.0947 | 0.1474 |
| 97.4964 | 0.75 | 1500 | 6.0419 | 0.1510 |
| 97.562 | 0.8 | 1600 | 6.0272 | 0.1518 |
| 97.3206 | 0.85 | 1700 | 6.0171 | 0.1529 |
| 96.8684 | 0.9 | 1800 | 6.0163 | 0.1532 |
| 96.472 | 0.95 | 1900 | 6.0193 | 0.1528 |
| 96.5051 | 1.0 | 2000 | 6.0191 | 0.1528 |
### Framework versions
- Transformers 4.56.0
- Pytorch 2.8.0+cu129
- Datasets 5.0.0
- Tokenizers 0.22.0
|