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library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: HybridModelScratch_lightn_Conti
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_lightn_Conti
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: 3.2749
- Accuracy: 0.3848
## 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: 0.001
- train_batch_size: 120
- eval_batch_size: 16
- seed: 42
- 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: 50000
### Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 4.5799 | 0.02 | 1000 | 0.2697 | 4.5051 |
| 4.1703 | 0.04 | 2000 | 0.3056 | 4.1036 |
| 4.0044 | 0.06 | 3000 | 0.3195 | 3.9451 |
| 3.8638 | 0.08 | 4000 | 0.3281 | 3.8499 |
| 3.7991 | 0.1 | 5000 | 0.3350 | 3.7702 |
| 3.6996 | 0.12 | 6000 | 0.3414 | 3.7112 |
| 3.6319 | 0.14 | 7000 | 0.3448 | 3.6666 |
| 3.6062 | 0.16 | 8000 | 0.3476 | 3.6405 |
| 3.6643 | 0.18 | 9000 | 0.3498 | 3.6175 |
| 3.5992 | 0.2 | 10000 | 0.3535 | 3.5797 |
| 3.5671 | 0.22 | 11000 | 0.3559 | 3.5543 |
| 3.5230 | 0.24 | 12000 | 0.3578 | 3.5308 |
| 3.5930 | 0.26 | 13000 | 0.3593 | 3.5190 |
| 3.5475 | 0.28 | 14000 | 0.3616 | 3.4961 |
| 3.5220 | 0.3 | 15000 | 0.3633 | 3.4778 |
| 3.5050 | 0.32 | 16000 | 0.3644 | 3.4654 |
| 3.4776 | 0.34 | 17000 | 0.3666 | 3.4458 |
| 3.4829 | 0.36 | 18000 | 0.3674 | 3.4346 |
| 3.4483 | 0.38 | 19000 | 0.3694 | 3.4189 |
| 3.4418 | 0.4 | 20000 | 0.3704 | 3.4063 |
| 3.4183 | 0.42 | 21000 | 0.3720 | 3.3956 |
| 3.3858 | 0.44 | 22000 | 0.3725 | 3.3870 |
| 3.3654 | 0.46 | 23000 | 0.3728 | 3.3824 |
| 3.3943 | 0.48 | 24000 | 0.3734 | 3.3756 |
| 3.3957 | 0.5 | 25000 | 0.3757 | 3.3548 |
| 3.3787 | 0.52 | 26000 | 0.3769 | 3.3452 |
| 3.3605 | 0.54 | 27000 | 0.3777 | 3.3393 |
| 3.3707 | 0.56 | 28000 | 0.3787 | 3.3302 |
| 3.3508 | 0.58 | 29000 | 0.3793 | 3.3221 |
| 3.3566 | 0.6 | 30000 | 0.3802 | 3.3148 |
| 3.3441 | 0.62 | 31000 | 0.3809 | 3.3054 |
| 3.3268 | 0.64 | 32000 | 0.3814 | 3.3028 |
| 3.0620 | 0.02 | 33000 | 3.3109 | 0.3804 |
| 3.0159 | 0.04 | 34000 | 3.3074 | 0.3810 |
| 3.0230 | 0.06 | 35000 | 3.3025 | 0.3815 |
| 3.0335 | 0.08 | 36000 | 3.2988 | 0.3821 |
| 3.0098 | 0.1 | 37000 | 3.2959 | 0.3826 |
| 3.0096 | 0.12 | 38000 | 3.2932 | 0.3826 |
| 2.9760 | 0.14 | 39000 | 3.2904 | 0.3831 |
| 2.9701 | 0.16 | 40000 | 3.2869 | 0.3832 |
| 2.9654 | 0.18 | 41000 | 3.2847 | 0.3837 |
| 2.9752 | 0.2 | 42000 | 3.2823 | 0.3839 |
| 2.9480 | 0.22 | 43000 | 3.2810 | 0.3840 |
| 2.9637 | 0.24 | 44000 | 3.2790 | 0.3842 |
| 2.9721 | 0.26 | 45000 | 3.2772 | 0.3843 |
| 2.9694 | 0.28 | 46000 | 3.2765 | 0.3847 |
| 2.9577 | 0.3 | 47000 | 3.2756 | 0.3847 |
| 2.9573 | 0.32 | 48000 | 3.2751 | 0.3847 |
| 2.9537 | 0.34 | 49000 | 3.2749 | 0.3848 |
| 2.9677 | 0.36 | 50000 | 3.2749 | 0.3848 |
### Framework versions
- Transformers 5.13.0
- Pytorch 2.8.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2
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