---
library_name: transformers
license: apache-2.0
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- alignment-handbook
- generated_from_trainer
datasets:
- data/ui_math_ref
- data/ui_coding_ref
model-index:
- name: tinyllama-1.1b-chat-v1.0-ui-math-coding-group-dpo
  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. -->

# tinyllama-1.1b-chat-v1.0-ui-math-coding-group-dpo

This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on the data/ui_math_ref and the data/ui_coding_ref datasets.
It achieves the following results on the evaluation set:
- Loss: 0.4193
- Rewards/chosen: -0.6057
- Rewards/rejected: -1.6972
- Rewards/accuracies: 0.7188
- Rewards/margins: 1.0915
- Logps/rejected: -538.1440
- Logps/chosen: -448.5587
- Logits/rejected: -2.6494
- Logits/chosen: -2.6509

## 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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 1024
- total_eval_batch_size: 128
- 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



### Framework versions

- Transformers 4.44.1
- Pytorch 2.1.2+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1