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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-3-Base-8B
  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-3-Base-8B

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: 0.6285
- Rewards/chosen: 0.5979
- Rewards/rejected: 0.1801
- Rewards/accuracies: 0.6620
- Rewards/margins: 0.4178
- Logps/rejected: -2212.5046
- Logps/chosen: -2612.9824
- Logits/rejected: -1.3033
- Logits/chosen: -1.3358

## 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: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6694        | 0.03  | 100  | 0.6733          | 0.4668         | 0.3687           | 0.5500             | 0.0980          | -2193.6436     | -2626.0984   | -1.2047         | -1.2463       |
| 0.6496        | 0.05  | 200  | 0.6497          | 0.8935         | 0.6578           | 0.6040             | 0.2357          | -2164.7385     | -2583.4270   | -1.1621         | -1.2030       |
| 0.6358        | 0.08  | 300  | 0.6672          | 0.6703         | 0.4436           | 0.5900             | 0.2266          | -2186.1528     | -2605.7471   | -1.2202         | -1.2617       |
| 0.6783        | 0.1   | 400  | 0.7144          | 0.2834         | 0.0925           | 0.5680             | 0.1909          | -2221.2676     | -2644.4390   | -1.3598         | -1.4017       |
| 0.751         | 0.13  | 500  | 0.6889          | 1.3453         | 0.9758           | 0.6020             | 0.3696          | -2132.9402     | -2538.2405   | -1.4750         | -1.5419       |
| 0.6921        | 0.16  | 600  | 0.6644          | 0.8464         | 0.5451           | 0.6220             | 0.3014          | -2176.0090     | -2588.1318   | -1.2841         | -1.3381       |
| 0.6437        | 0.18  | 700  | 0.6724          | 0.8250         | 0.4796           | 0.6420             | 0.3454          | -2182.5566     | -2590.2764   | -1.4526         | -1.4817       |
| 0.8109        | 0.21  | 800  | 0.6655          | 1.1490         | 0.7473           | 0.6380             | 0.4017          | -2155.7832     | -2557.8708   | -1.5267         | -1.5761       |
| 0.6725        | 0.24  | 900  | 0.6836          | 1.4258         | 0.9989           | 0.6160             | 0.4269          | -2130.6240     | -2530.1914   | -1.4486         | -1.4910       |
| 0.7027        | 0.26  | 1000 | 0.6690          | 0.8152         | 0.4729           | 0.6260             | 0.3424          | -2183.2278     | -2591.2505   | -1.5095         | -1.5565       |
| 0.6421        | 0.29  | 1100 | 0.6513          | 0.5281         | 0.1941           | 0.6640             | 0.3340          | -2211.1040     | -2619.9661   | -1.5382         | -1.5785       |
| 0.6217        | 0.31  | 1200 | 0.6436          | 0.7372         | 0.3396           | 0.6460             | 0.3976          | -2196.5581     | -2599.0544   | -1.6345         | -1.6765       |
| 0.7365        | 0.34  | 1300 | 0.6400          | 0.9183         | 0.5227           | 0.6240             | 0.3956          | -2178.2437     | -2580.9446   | -1.5597         | -1.6009       |
| 0.7057        | 0.37  | 1400 | 0.6468          | 0.9514         | 0.5619           | 0.6140             | 0.3895          | -2174.3254     | -2577.6377   | -1.6716         | -1.7117       |
| 0.6396        | 0.39  | 1500 | 0.6498          | 0.9546         | 0.5405           | 0.6400             | 0.4141          | -2176.4675     | -2577.3193   | -1.6244         | -1.6600       |
| 0.5835        | 0.42  | 1600 | 0.6488          | 0.9504         | 0.5356           | 0.6480             | 0.4148          | -2176.9568     | -2577.7402   | -1.6255         | -1.6706       |
| 0.629         | 0.44  | 1700 | 0.6501          | 1.2484         | 0.8056           | 0.6100             | 0.4428          | -2149.9568     | -2547.9316   | -1.5737         | -1.6192       |
| 0.6495        | 0.47  | 1800 | 0.6440          | 1.2029         | 0.7629           | 0.6280             | 0.4400          | -2154.2307     | -2552.4846   | -1.4589         | -1.4973       |
| 0.6465        | 0.5   | 1900 | 0.6641          | 0.2111         | -0.0941          | 0.6280             | 0.3052          | -2239.9255     | -2651.6641   | -1.4961         | -1.5323       |
| 0.6866        | 0.52  | 2000 | 0.6480          | 0.5747         | 0.1977           | 0.6600             | 0.3770          | -2210.75       | -2615.3054   | -1.4509         | -1.4934       |
| 0.6441        | 0.55  | 2100 | 0.6358          | 0.8809         | 0.4502           | 0.6480             | 0.4307          | -2185.4985     | -2584.6841   | -1.4418         | -1.4842       |
| 0.6752        | 0.58  | 2200 | 0.6346          | 0.9311         | 0.5075           | 0.6560             | 0.4236          | -2179.7668     | -2579.6636   | -1.3193         | -1.3656       |
| 0.5646        | 0.6   | 2300 | 0.6396          | 0.6599         | 0.2912           | 0.6480             | 0.3686          | -2201.3948     | -2606.7883   | -1.2832         | -1.3116       |
| 0.6519        | 0.63  | 2400 | 0.6451          | 0.4237         | 0.0937           | 0.6400             | 0.3300          | -2221.1460     | -2630.4050   | -1.4460         | -1.4777       |
| 0.6292        | 0.65  | 2500 | 0.6313          | 0.8682         | 0.4231           | 0.6460             | 0.4452          | -2188.2095     | -2585.9512   | -1.4040         | -1.4397       |
| 0.5985        | 0.68  | 2600 | 0.6274          | 0.8396         | 0.3650           | 0.6640             | 0.4746          | -2194.0144     | -2588.8174   | -1.3580         | -1.3860       |
| 0.6323        | 0.71  | 2700 | 0.6328          | 0.6585         | 0.2012           | 0.6640             | 0.4573          | -2210.3958     | -2606.9260   | -1.2622         | -1.2938       |
| 0.6174        | 0.73  | 2800 | 0.6305          | 0.8505         | 0.3762           | 0.6580             | 0.4744          | -2192.8989     | -2587.7209   | -1.3312         | -1.3635       |
| 0.5972        | 0.76  | 2900 | 0.6310          | 0.6521         | 0.2290           | 0.6600             | 0.4231          | -2207.6130     | -2607.5659   | -1.3492         | -1.3840       |
| 0.6645        | 0.79  | 3000 | 0.6291          | 0.7035         | 0.2579           | 0.6520             | 0.4456          | -2204.7251     | -2602.4238   | -1.3330         | -1.3678       |
| 0.5786        | 0.81  | 3100 | 0.6310          | 0.5452         | 0.1222           | 0.6580             | 0.4230          | -2218.2944     | -2618.2534   | -1.3173         | -1.3498       |
| 0.604         | 0.84  | 3200 | 0.6375          | 0.3327         | -0.0527          | 0.6540             | 0.3854          | -2235.7852     | -2639.5032   | -1.3444         | -1.3760       |
| 0.6704        | 0.86  | 3300 | 0.6269          | 0.7327         | 0.2896           | 0.6540             | 0.4431          | -2201.5579     | -2599.5049   | -1.3241         | -1.3585       |
| 0.6365        | 0.89  | 3400 | 0.6271          | 0.6900         | 0.2577           | 0.6560             | 0.4323          | -2204.7437     | -2603.7739   | -1.3038         | -1.3371       |
| 0.6621        | 0.92  | 3500 | 0.6279          | 0.6303         | 0.2073           | 0.6580             | 0.4230          | -2209.7827     | -2609.7432   | -1.2991         | -1.3321       |
| 0.6597        | 0.94  | 3600 | 0.6294          | 0.5540         | 0.1441           | 0.6580             | 0.4099          | -2216.1082     | -2617.3774   | -1.3028         | -1.3348       |
| 0.671         | 0.97  | 3700 | 0.6285          | 0.5945         | 0.1774           | 0.6600             | 0.4171          | -2212.7783     | -2613.3303   | -1.3033         | -1.3358       |
| 0.6328        | 0.99  | 3800 | 0.6283          | 0.5985         | 0.1803           | 0.6580             | 0.4182          | -2212.4902     | -2612.9258   | -1.3032         | -1.3356       |


### Framework versions

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