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license: llama3.1
base_model: meta-llama/Llama-3.1-8B-Instruct
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: llama3_rm
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. -->
# llama3_rm
This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3742
- Accuracy: 0.8948
## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.6626 | 0.0705 | 10 | 0.5923 | 0.6719 |
| 0.5039 | 0.1410 | 20 | 0.5139 | 0.7568 |
| 0.4865 | 0.2115 | 30 | 0.4816 | 0.7646 |
| 0.4814 | 0.2819 | 40 | 0.4566 | 0.7891 |
| 0.4932 | 0.3524 | 50 | 0.4449 | 0.7979 |
| 0.4723 | 0.4229 | 60 | 0.4267 | 0.8031 |
| 0.3906 | 0.4934 | 70 | 0.4042 | 0.8208 |
| 0.3418 | 0.5639 | 80 | 0.3907 | 0.8245 |
| 0.4427 | 0.6344 | 90 | 0.3736 | 0.8359 |
| 0.4022 | 0.7048 | 100 | 0.3578 | 0.8484 |
| 0.3738 | 0.7753 | 110 | 0.3470 | 0.8542 |
| 0.3619 | 0.8458 | 120 | 0.3328 | 0.8609 |
| 0.3266 | 0.9163 | 130 | 0.3256 | 0.8651 |
| 0.2786 | 0.9868 | 140 | 0.3245 | 0.8693 |
| 0.1685 | 1.0573 | 150 | 0.4035 | 0.8786 |
| 0.0421 | 1.1278 | 160 | 0.4395 | 0.8823 |
| 0.0655 | 1.1982 | 170 | 0.3843 | 0.8828 |
| 0.0734 | 1.2687 | 180 | 0.3645 | 0.8823 |
| 0.1441 | 1.3392 | 190 | 0.4277 | 0.8833 |
| 0.1176 | 1.4097 | 200 | 0.4040 | 0.8896 |
| 0.0826 | 1.4802 | 210 | 0.3609 | 0.8870 |
| 0.056 | 1.5507 | 220 | 0.3542 | 0.8891 |
| 0.0487 | 1.6211 | 230 | 0.3668 | 0.8927 |
| 0.0815 | 1.6916 | 240 | 0.3735 | 0.8938 |
| 0.0842 | 1.7621 | 250 | 0.3751 | 0.8943 |
| 0.0868 | 1.8326 | 260 | 0.3758 | 0.8932 |
| 0.0743 | 1.9031 | 270 | 0.3753 | 0.8938 |
| 0.0874 | 1.9736 | 280 | 0.3742 | 0.8948 |
### Framework versions
- Transformers 4.43.4
- Pytorch 2.1.2+cu121
- Datasets 4.4.1
- Tokenizers 0.19.1
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