---
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
- generated_from_trainer
datasets:
- data/ui_math
model-index:
- name: tinyllama-1.1b-chat-v1.0-ui-math-dpo
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# tinyllama-1.1b-chat-v1.0-ui-math-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 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6894
- Rewards/chosen: -0.8659
- Rewards/rejected: -0.8634
- Rewards/accuracies: 0.625
- Rewards/margins: -0.0025
- Logps/rejected: -327.4781
- Logps/chosen: -342.2401
- Logits/rejected: -1.8881
- Logits/chosen: -2.0022

## 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