| Quantization made by Richard Erkhov. | |
| [Github](https://github.com/RichardErkhov) | |
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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: [] | |
| --- | |
| <!-- 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-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 | |