---
library_name: transformers
base_model: llama_small_config.json
tags:
- generated_from_trainer
model-index:
- name: llama-3.2-350M-fourier_arithmetic_dataset
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# llama-3.2-350M-fourier_arithmetic_dataset

This model is a fine-tuned version of [llama_small_config.json](https://huggingface.co/llama_small_config.json) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6047

## 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: 0.0005
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- total_eval_batch_size: 2
- optimizer: Use adamw_torch 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: 1000
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.8493        | 0.1066 | 1000 | 1.8628          |
| 1.8654        | 0.2132 | 2000 | 1.8692          |
| 1.8328        | 0.3197 | 3000 | 1.8328          |
| 1.7287        | 0.4263 | 4000 | 1.7136          |
| 1.6856        | 0.5329 | 5000 | 1.6816          |
| 1.65          | 0.6395 | 6000 | 1.6494          |
| 1.6304        | 0.7460 | 7000 | 1.6308          |
| 1.6071        | 0.8526 | 8000 | 1.6119          |
| 1.6022        | 0.9592 | 9000 | 1.6047          |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.3.1+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0