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---
base_model: Minbyul/selfbiorag-7b-wo-live_qa-sft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: selfbiorag-7b-dpo-full-sft-wo-live_qa
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. -->
# selfbiorag-7b-dpo-full-sft-wo-live_qa
This model is a fine-tuned version of [Minbyul/selfbiorag-7b-wo-live_qa-sft](https://huggingface.co/Minbyul/selfbiorag-7b-wo-live_qa-sft) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1422
- Rewards/chosen: -1.2709
- Rewards/rejected: -13.2633
- Rewards/accuracies: 0.9167
- Rewards/margins: 11.9924
- Logps/rejected: -1991.3534
- Logps/chosen: -456.8682
- Logits/rejected: -0.4049
- Logits/chosen: -0.4878
## 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-06
- 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
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.2635 | 0.3 | 100 | 0.1990 | -0.5114 | -9.8179 | 0.9167 | 9.3065 | -1646.8138 | -380.9204 | -0.1085 | -0.3091 |
| 0.1415 | 0.61 | 200 | 0.1502 | -0.9081 | -11.0651 | 0.9167 | 10.1570 | -1771.5302 | -420.5836 | -0.4280 | -0.4824 |
| 0.0892 | 0.91 | 300 | 0.1421 | -1.2604 | -13.2286 | 0.9167 | 11.9683 | -1987.8828 | -455.8129 | -0.4048 | -0.4887 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2
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