---
library_name: transformers
base_model: W-61/llama-3-8b-base-sft-ultrachat-8xh200
tags:
- alignment-handbook
- kto
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: llama-3-8b-base-kto-ultrafeedback-8xh200
  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-3-8b-base-kto-ultrafeedback-8xh200

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: 0.3658
- Rewards/chosen: 0.1622
- Logps/chosen: -286.2337
- Rewards/rejected: -2.5444
- Logps/rejected: -292.3963
- Rewards/margins: 2.7066
- Kl: 0.0
- Logits/chosen: -140467840.0
- Logits/rejected: -139209600.0

## 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: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- 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 | Logps/chosen | Rewards/rejected | Logps/rejected | Rewards/margins | Kl  | Logits/chosen | Logits/rejected |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:------------:|:----------------:|:--------------:|:---------------:|:---:|:-------------:|:---------------:|
| 1.5841        | 0.2094 | 200  | 0.3971          | -0.1699        | -289.5548    | -1.7146          | -284.0978      | 1.5447          | 0.0 | -151004736.0  | -149476768.0    |
| 1.404         | 0.4188 | 400  | 0.3773          | -0.0342        | -288.1983    | -2.3874          | -290.8255      | 2.3531          | 0.0 | -143785152.0  | -142386976.0    |
| 1.4253        | 0.6283 | 600  | 0.3684          | -0.3211        | -291.0670    | -3.1407          | -298.3589      | 2.8196          | 0.0 | -145117536.0  | -143700400.0    |
| 1.4432        | 0.8377 | 800  | 0.3658          | 0.1622         | -286.2337    | -2.5444          | -292.3963      | 2.7066          | 0.0 | -140467840.0  | -139209600.0    |


### Framework versions

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