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---
library_name: transformers
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
- alignment-handbook
- trl
- cpo
- generated_from_trainer
- trl
- cpo
- generated_from_trainer
datasets:
- princeton-nlp/llama3-ultrafeedback
model-index:
- name: llama3.1-cpo-full-0912
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. -->
# llama3.1-cpo-full-0912
This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the princeton-nlp/llama3-ultrafeedback dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5985
- Rewards/chosen: -15.4365
- Rewards/rejected: -16.1367
- Rewards/accuracies: 0.6239
- Rewards/margins: 0.7002
- Logps/rejected: -161.3668
- Logps/chosen: -154.3647
- Logits/rejected: -0.3853
- Logits/chosen: -0.4112
- Nll Loss: 0.4210
## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|
| 1.9362 | 0.2311 | 100 | 1.7930 | -14.9339 | -15.2848 | 0.5761 | 0.3508 | -152.8475 | -149.3394 | -0.4123 | -0.4378 | 0.4067 |
| 1.7019 | 0.4623 | 200 | 1.6786 | -15.4303 | -16.0131 | 0.6087 | 0.5828 | -160.1311 | -154.3027 | -0.3358 | -0.3580 | 0.4193 |
| 1.6388 | 0.6934 | 300 | 1.6233 | -15.5465 | -16.2127 | 0.6130 | 0.6662 | -162.1269 | -155.4650 | -0.3582 | -0.3828 | 0.4230 |
| 1.632 | 0.9246 | 400 | 1.6007 | -15.6505 | -16.3448 | 0.6370 | 0.6943 | -163.4479 | -156.5048 | -0.3811 | -0.4072 | 0.4277 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.3.1
- Datasets 2.21.0
- Tokenizers 0.19.1
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