---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: Aris-140M
  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. -->

# Aris-140M

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: 3.3110

## 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: 0.00025
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- total_eval_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 200
- training_steps: 7630

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 5.0026        | 0.0655 | 500  | 4.9335          |
| 4.1512        | 0.1311 | 1000 | 4.1450          |
| 3.9029        | 0.1966 | 1500 | 3.8596          |
| 3.7558        | 0.2621 | 2000 | 3.7075          |
| 3.5920        | 0.3277 | 2500 | 3.6100          |
| 3.5657        | 0.3932 | 3000 | 3.5328          |
| 3.4994        | 0.4587 | 3500 | 3.4764          |
| 3.4811        | 0.5242 | 4000 | 3.4332          |
| 3.4043        | 0.5898 | 4500 | 3.3970          |
| 3.3963        | 0.6553 | 5000 | 3.3697          |
| 3.3784        | 0.7208 | 5500 | 3.3471          |
| 3.3817        | 0.7864 | 6000 | 3.3304          |
| 3.3694        | 0.8519 | 6500 | 3.3189          |
| 3.3337        | 0.9174 | 7000 | 3.3129          |
| 3.3679        | 0.9830 | 7500 | 3.3111          |
| 3.3503        | 1.0    | 7630 | 3.3110          |


### Framework versions

- Transformers 5.12.1
- Pytorch 2.6.0+cu124
- Datasets 5.0.0
- Tokenizers 0.22.2