---
library_name: transformers
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: oh_scale_x.5_compute_equal
  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. -->

# oh_scale_x.5_compute_equal

This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B) on the mlfoundations-dev/oh-dcft-v1.3_no-curation_gpt-4o-mini_scale_0.5x dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4058

## 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: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- total_eval_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 25.0

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.7807        | 0.9947  | 165  | 0.7690          |
| 0.7139        | 1.9955  | 331  | 0.7520          |
| 0.6642        | 2.9962  | 497  | 0.7525          |
| 0.6186        | 3.9970  | 663  | 0.7615          |
| 0.5777        | 4.9977  | 829  | 0.7785          |
| 0.5287        | 5.9985  | 995  | 0.8154          |
| 0.473         | 6.9992  | 1161 | 0.8710          |
| 0.4134        | 8.0     | 1327 | 0.9475          |
| 0.3615        | 8.9947  | 1492 | 1.0203          |
| 0.3057        | 9.9955  | 1658 | 1.1177          |
| 0.2565        | 10.9962 | 1824 | 1.2368          |
| 0.2099        | 11.9970 | 1990 | 1.3552          |
| 0.1676        | 12.9977 | 2156 | 1.5071          |
| 0.1283        | 13.9985 | 2322 | 1.6324          |
| 0.1022        | 14.9992 | 2488 | 1.7542          |
| 0.0779        | 16.0    | 2654 | 1.8729          |
| 0.0607        | 16.9947 | 2819 | 1.9862          |
| 0.0481        | 17.9955 | 2985 | 2.0547          |
| 0.038         | 18.9962 | 3151 | 2.1351          |
| 0.0306        | 19.9970 | 3317 | 2.2255          |
| 0.0256        | 20.9977 | 3483 | 2.2699          |
| 0.0221        | 21.9985 | 3649 | 2.3515          |
| 0.0197        | 22.9992 | 3815 | 2.3599          |
| 0.0186        | 24.0    | 3981 | 2.3888          |
| 0.0169        | 24.8681 | 4125 | 2.4058          |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.3.0
- Datasets 3.1.0
- Tokenizers 0.20.3