---
library_name: transformers
base_model: aubmindlab/aragpt2-base
tags:
- generated_from_trainer
model-index:
- name: aragpt2-transport-autocomplete
  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. -->

# aragpt2-transport-autocomplete

This model is a fine-tuned version of [aubmindlab/aragpt2-base](https://huggingface.co/aubmindlab/aragpt2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5047

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 6.9371        | 1.1236 | 100  | 5.0896          |
| 3.5858        | 2.2472 | 200  | 2.8953          |
| 2.3939        | 3.3708 | 300  | 2.4553          |
| 1.7935        | 4.4944 | 400  | 2.4373          |
| 1.4304        | 5.6180 | 500  | 2.3790          |
| 1.2880        | 6.7416 | 600  | 2.4508          |
| 1.0935        | 7.8652 | 700  | 2.5212          |
| 1.1357        | 8.9888 | 800  | 2.5047          |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2