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---
library_name: peft
tags:
- trl
- orpo
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B-Instruct
model-index:
- name: results
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/52g/huggingface/runs/xlq51xa8)
# results
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0888
- Rewards/chosen: -0.0906
- Rewards/rejected: -0.1196
- Rewards/accuracies: 0.8000
- Rewards/margins: 0.0290
- Logps/rejected: -1.1960
- Logps/chosen: -0.9064
- Logits/rejected: -1.3083
- Logits/chosen: -1.0410
- Nll Loss: 1.0376
- Log Odds Ratio: -0.5127
- Log Odds Chosen: 0.4766
## 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: 8e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.0958 | 0.2020 | 25 | 1.4462 | -0.1303 | -0.1689 | 0.8000 | 0.0386 | -1.6887 | -1.3025 | -1.1831 | -0.9153 | 1.3976 | -0.4854 | 0.5211 |
| 1.2563 | 0.4040 | 50 | 1.2116 | -0.1057 | -0.1387 | 0.8000 | 0.0330 | -1.3872 | -1.0575 | -1.2714 | -1.0083 | 1.1616 | -0.5001 | 0.4913 |
| 1.3121 | 0.6061 | 75 | 1.1251 | -0.0952 | -0.1249 | 0.9000 | 0.0297 | -1.2491 | -0.9524 | -1.3022 | -1.0390 | 1.0740 | -0.5109 | 0.4726 |
| 1.3689 | 0.8081 | 100 | 1.0888 | -0.0906 | -0.1196 | 0.8000 | 0.0290 | -1.1960 | -0.9064 | -1.3083 | -1.0410 | 1.0376 | -0.5127 | 0.4766 |
### Framework versions
- PEFT 0.10.1.dev0
- Transformers 4.41.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1 |