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---
base_model: princeton-nlp/Llama-3-Base-8B-SFT
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: llama-8b-dpo-full
  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. -->

# llama-8b-dpo-full

This model is a fine-tuned version of [princeton-nlp/Llama-3-Base-8B-SFT](https://huggingface.co/princeton-nlp/Llama-3-Base-8B-SFT) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6316
- Rewards/chosen: 0.6899
- Rewards/rejected: 0.3044
- Rewards/accuracies: 0.6600
- Rewards/margins: 0.3855
- Logps/rejected: -2200.0752
- Logps/chosen: -2603.7832
- Logits/rejected: -1.4288
- Logits/chosen: -1.4752

## 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: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6558        | 0.05  | 100  | 0.6527          | 0.7712         | 0.5799           | 0.5740             | 0.1913          | -2172.5291     | -2595.6543   | -1.1822         | -1.2241       |
| 0.6404        | 0.1   | 200  | 0.6911          | 0.4590         | 0.2677           | 0.5860             | 0.1913          | -2203.7483     | -2626.8760   | -1.2019         | -1.2423       |
| 0.6725        | 0.16  | 300  | 0.6603          | 0.8108         | 0.5231           | 0.6320             | 0.2877          | -2178.2058     | -2591.6921   | -1.3149         | -1.3646       |
| 0.689         | 0.21  | 400  | 0.6529          | 0.8101         | 0.4993           | 0.6280             | 0.3108          | -2180.5830     | -2591.7649   | -1.4428         | -1.5029       |
| 0.6682        | 0.26  | 500  | 0.6674          | 0.9667         | 0.6125           | 0.6420             | 0.3542          | -2169.2654     | -2576.1008   | -1.5148         | -1.5665       |
| 0.6309        | 0.31  | 600  | 0.6445          | 0.8348         | 0.4673           | 0.6580             | 0.3675          | -2183.7852     | -2589.2971   | -1.5885         | -1.6449       |
| 0.6467        | 0.37  | 700  | 0.6482          | 0.8852         | 0.5455           | 0.6240             | 0.3397          | -2175.9651     | -2584.2512   | -1.6562         | -1.7105       |
| 0.6215        | 0.42  | 800  | 0.6453          | 1.0902         | 0.6825           | 0.6380             | 0.4077          | -2162.2678     | -2563.7546   | -1.6541         | -1.7085       |
| 0.6674        | 0.47  | 900  | 0.6416          | 0.7802         | 0.4490           | 0.6440             | 0.3312          | -2185.6135     | -2594.7568   | -1.5145         | -1.5652       |
| 0.644         | 0.52  | 1000 | 0.6500          | 0.7077         | 0.3679           | 0.6400             | 0.3398          | -2193.7285     | -2602.0039   | -1.4506         | -1.5047       |
| 0.6539        | 0.58  | 1100 | 0.6389          | 0.8477         | 0.4852           | 0.6500             | 0.3625          | -2181.9937     | -2588.0068   | -1.4697         | -1.5227       |
| 0.7267        | 0.63  | 1200 | 0.6421          | 0.5390         | 0.2257           | 0.6620             | 0.3133          | -2207.9438     | -2618.8738   | -1.6292         | -1.6800       |
| 0.5746        | 0.68  | 1300 | 0.6301          | 0.9057         | 0.4892           | 0.6660             | 0.4164          | -2181.5920     | -2582.2095   | -1.4994         | -1.5461       |
| 0.6053        | 0.73  | 1400 | 0.6342          | 0.8758         | 0.4563           | 0.6660             | 0.4196          | -2184.8909     | -2585.1914   | -1.4440         | -1.4891       |
| 0.6232        | 0.79  | 1500 | 0.6324          | 0.8055         | 0.3994           | 0.6580             | 0.4062          | -2190.5796     | -2592.2219   | -1.4283         | -1.4759       |
| 0.6326        | 0.84  | 1600 | 0.6392          | 0.4525         | 0.1032           | 0.6560             | 0.3493          | -2220.1997     | -2627.5283   | -1.4501         | -1.4959       |
| 0.6469        | 0.89  | 1700 | 0.6306          | 0.7453         | 0.3498           | 0.6660             | 0.3955          | -2195.5359     | -2598.2412   | -1.4289         | -1.4758       |
| 0.669         | 0.94  | 1800 | 0.6323          | 0.6544         | 0.2748           | 0.6600             | 0.3796          | -2203.0393     | -2607.3367   | -1.4308         | -1.4769       |
| 0.6531        | 0.99  | 1900 | 0.6317          | 0.6900         | 0.3040           | 0.6640             | 0.3860          | -2200.1182     | -2603.7776   | -1.4289         | -1.4754       |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2