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---
base_model: meta-llama/Meta-Llama-3-8B-Instruct
library_name: peft
license: llama3
tags:
- trl
- orpo
- generated_from_trainer
model-index:
- name: OrpoLlama-3-8B-Instruct
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. -->
# OrpoLlama-3-8B-Instruct
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: 1.1648
- Rewards/chosen: -0.0603
- Rewards/rejected: -0.0824
- Rewards/accuracies: 0.5
- Rewards/margins: 0.0221
- Logps/rejected: -0.8240
- Logps/chosen: -0.6033
- Logits/rejected: -0.1024
- Logits/chosen: -0.2381
- Nll Loss: 1.1016
- Log Odds Ratio: -0.6324
- Log Odds Chosen: 0.4547
## 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: 3
### 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 0.95 | 0.5980 | 74 | 1.2436 | -0.0675 | -0.0830 | 0.4000 | 0.0155 | -0.8295 | -0.6746 | -0.2051 | -0.3444 | 1.1740 | -0.6961 | 0.2761 |
| 0.9613 | 1.1960 | 148 | 1.1952 | -0.0621 | -0.0799 | 0.4000 | 0.0179 | -0.7994 | -0.6209 | -0.1256 | -0.2699 | 1.1280 | -0.6717 | 0.3516 |
| 1.5258 | 1.7939 | 222 | 1.1740 | -0.0609 | -0.0818 | 0.5 | 0.0209 | -0.8183 | -0.6094 | -0.1255 | -0.2648 | 1.1099 | -0.6414 | 0.4267 |
| 1.1971 | 2.3919 | 296 | 1.1648 | -0.0603 | -0.0824 | 0.5 | 0.0221 | -0.8240 | -0.6033 | -0.1024 | -0.2381 | 1.1016 | -0.6324 | 0.4547 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1 |