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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-0913
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-0913
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: 1.4404
- Rewards/chosen: -16.0845
- Rewards/rejected: -16.8741
- Rewards/accuracies: 0.6326
- Rewards/margins: 0.7896
- Logps/rejected: -168.7413
- Logps/chosen: -160.8449
- Logits/rejected: -0.3487
- Logits/chosen: -0.3704
- Nll Loss: 0.2790
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|
| 1.7833 | 0.2311 | 100 | 1.6389 | -15.3939 | -15.7792 | 0.5783 | 0.3853 | -157.7921 | -153.9390 | -0.3065 | -0.3333 | 0.2678 |
| 1.5321 | 0.4623 | 200 | 1.5242 | -15.8988 | -16.5121 | 0.5978 | 0.6132 | -165.1206 | -158.9884 | -0.4244 | -0.4423 | 0.2764 |
| 1.4722 | 0.6934 | 300 | 1.4633 | -16.0803 | -16.8141 | 0.6217 | 0.7338 | -168.1411 | -160.8031 | -0.3641 | -0.3856 | 0.2790 |
| 1.4589 | 0.9246 | 400 | 1.4447 | -16.0215 | -16.8041 | 0.6261 | 0.7826 | -168.0413 | -160.2150 | -0.3389 | -0.3606 | 0.2798 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.3.1
- Datasets 2.21.0
- Tokenizers 0.19.1
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