---
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-4xh200-batch-128-20260427-194056
  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-4xh200-batch-128-20260427-194056

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: 0.4319
- Rewards/chosen: -0.5716
- Logps/chosen: -345.0196
- Rewards/rejected: -1.4489
- Logps/rejected: -411.8449
- Rewards/margins: 0.8773
- Kl: 0.0
- Logits/chosen: -377414720.0
- Logits/rejected: -376930848.0

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:------------:|:----------------:|:--------------:|:---------------:|:---:|:-------------:|:---------------:|
| 1.8447        | 0.2094 | 200  | 0.4646          | -0.6301        | -350.8658    | -0.9983          | -366.7805      | 0.3682          | 0.0 | -401673280.0  | -397073248.0    |
| 1.7296        | 0.4188 | 400  | 0.4408          | -0.6904        | -356.8998    | -1.3983          | -406.7836      | 0.7079          | 0.0 | -377831392.0  | -377408832.0    |
| 1.685         | 0.6283 | 600  | 0.4325          | -0.9586        | -383.711     | -1.8718          | -454.1356      | 0.9133          | 0.0 | -388254240.0  | -387494368.0    |
| 1.7464        | 0.8377 | 800  | 0.4319          | -0.5716        | -345.0196    | -1.4489          | -411.8449      | 0.8773          | 0.0 | -377414720.0  | -376930848.0    |


### Framework versions

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