---
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