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---
library_name: transformers
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: Llama0-3-8b-ultra-p-0.05-lr1e-6-e1
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. -->
# Llama0-3-8b-ultra-p-0.05-lr1e-6-e1
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: 0.5155
- Rewards/chosen: -0.8052
- Rewards/rejected: -1.6601
- Rewards/accuracies: 0.75
- Rewards/margins: 0.8549
- Logps/rejected: -430.6040
- Logps/chosen: -337.1520
- Logits/rejected: 0.5600
- Logits/chosen: 0.4444
## 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: 1e-06
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5887 | 0.2060 | 100 | 0.5813 | -0.4118 | -0.7745 | 0.6875 | 0.3628 | -342.0493 | -297.8121 | 0.1168 | 0.0514 |
| 0.5536 | 0.4119 | 200 | 0.5446 | -0.6533 | -1.3097 | 0.7031 | 0.6564 | -395.5632 | -321.9608 | 0.3951 | 0.2772 |
| 0.5319 | 0.6179 | 300 | 0.5262 | -0.6809 | -1.4161 | 0.7344 | 0.7353 | -406.2091 | -324.7231 | 0.4856 | 0.3738 |
| 0.5268 | 0.8239 | 400 | 0.5195 | -0.7599 | -1.5725 | 0.7344 | 0.8126 | -421.8436 | -332.6288 | 0.5181 | 0.3998 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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