README.md

Quantization made by Richard Erkhov.

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tinyllama-1.1b-mt-dpo-full_LR5e-8_BS16_rmsprop_2epochs - AWQ
- Model creator: https://huggingface.co/martimfasantos/
- Original model: https://huggingface.co/martimfasantos/tinyllama-1.1b-mt-dpo-full_LR5e-8_BS16_rmsprop_2epochs/




Original model description:
---
license: apache-2.0
base_model: martimfasantos/tinyllama-1.1b-mt-sft-full
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- haoranxu/ALMA-R-Preference
model-index:
- name: tinyllama-1.1b-mt-dpo-full_LR5e-8_BS16_rmsprop_2epochs
  results: []
---

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# tinyllama-1.1b-mt-dpo-full_LR5e-8_BS16_rmsprop_2epochs

This model is a fine-tuned version of [martimfasantos/tinyllama-1.1b-mt-sft-full](https://huggingface.co/martimfasantos/tinyllama-1.1b-mt-sft-full) on the haoranxu/ALMA-R-Preference dataset.

## 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-08
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2

### Training results



### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1