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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_j-full-0911
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_j-full-0911
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: 1.4373
- Rewards/chosen: -14.1493
- Rewards/rejected: -15.5710
- Rewards/accuracies: 0.6543
- Rewards/margins: 1.4217
- Logps/rejected: -155.7095
- Logps/chosen: -141.4926
- Logits/rejected: -0.1136
- Logits/chosen: -0.1476
- Nll Loss: 0.1725
## 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: 5
### 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|
| 1.4367 | 0.9986 | 432 | 1.3926 | -17.0679 | -18.0962 | 0.6565 | 1.0283 | -180.9624 | -170.6792 | -0.4080 | -0.4373 | 0.3200 |
| 0.5472 | 1.9994 | 865 | 1.2973 | -16.2909 | -17.5852 | 0.6587 | 1.2944 | -175.8523 | -162.9086 | -0.5434 | -0.5688 | 0.2148 |
| 0.2244 | 2.9980 | 1297 | 1.3861 | -15.7105 | -17.2195 | 0.6565 | 1.5089 | -172.1945 | -157.1052 | -0.3428 | -0.3715 | 0.2034 |
| 0.1472 | 3.9988 | 1730 | 1.4029 | -14.6462 | -16.1385 | 0.6522 | 1.4923 | -161.3849 | -146.4623 | -0.2701 | -0.3029 | 0.1876 |
| 0.1143 | 4.9928 | 2160 | 1.4373 | -14.1493 | -15.5710 | 0.6543 | 1.4217 | -155.7095 | -141.4926 | -0.1136 | -0.1476 | 0.1725 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.3.1
- Datasets 2.21.0
- Tokenizers 0.19.1
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