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---
license: apache-2.0
base_model: Minbyul/biomistral-7b-wo-kqa_golden-iter-dpo-step1
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: biomistral-7b-wo-kqa_golden-iter-dpo-step2
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. -->
# biomistral-7b-wo-kqa_golden-iter-dpo-step2
This model is a fine-tuned version of [Minbyul/biomistral-7b-wo-kqa_golden-iter-dpo-step1](https://huggingface.co/Minbyul/biomistral-7b-wo-kqa_golden-iter-dpo-step1) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6909
- Rewards/chosen: 0.0063
- Rewards/rejected: 0.0057
- Rewards/accuracies: 0.5625
- Rewards/margins: 0.0006
- Logps/rejected: -193.8717
- Logps/chosen: -168.4928
- Logits/rejected: -2.2060
- Logits/chosen: -2.9391
## 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: 1e-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- 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 4.38.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2
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