---
library_name: transformers
base_model: W-61/llama-3-8b-base-sft-ultrachat-8xh200
tags:
- alignment-handbook
- ipo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: llama-3-8b-base-ipo-ultrafeedback-4xh200-batch-128
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# llama-3-8b-base-ipo-ultrafeedback-4xh200-batch-128

This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-ultrachat-8xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-ultrachat-8xh200) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 2331.0774
- Rewards/chosen: -0.0345
- Rewards/rejected: -0.0581
- Rewards/accuracies: 0.6880
- Rewards/margins: 0.0236
- Logps/rejected: -7.1047
- Logps/chosen: -4.5678
- Logits/rejected: -0.4255
- Logits/chosen: -0.4244

## 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: 5e-07
- 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 19252.4328    | 0.4188 | 200  | 2421.5791       | -0.0163        | -0.0243          | 0.6360             | 0.0080          | -3.7316        | -2.7498      | -0.6321         | -0.6354       |
| 18622.8812    | 0.8377 | 400  | 2331.0774       | -0.0345        | -0.0581          | 0.6880             | 0.0236          | -7.1047        | -4.5678      | -0.4255         | -0.4244       |


### Framework versions

- Transformers 4.51.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.4