---
base_model: jetmoe/jetmoe-8b-sft
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: jetmoe-8b-chat
  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. -->

# jetmoe-8b-chat

This model is a fine-tuned version of [jetmoe-8b-sft](https://huggingface.co/jetmoe/jetmoe-8b-sft) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6372
- Rewards/chosen: -0.0901
- Rewards/rejected: -0.2250
- Rewards/accuracies: 0.7148
- Rewards/margins: 0.1349
- Logps/rejected: -289.3396
- Logps/chosen: -286.2378
- Logits/rejected: -2.9020
- Logits/chosen: -2.9443

## 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: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6664        | 0.42  | 200  | 0.6622          | -0.0185        | -0.0869          | 0.6997             | 0.0684          | -275.5274      | -279.0778    | -2.9127         | -2.9572       |
| 0.6428        | 0.84  | 400  | 0.6372          | -0.0901        | -0.2250          | 0.7148             | 0.1349          | -289.3396      | -286.2378    | -2.9020         | -2.9443       |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2