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---
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library_name: transformers
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license: apache-2.0
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base_model: Qwen/Qwen2.5-14B-Instruct
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tags:
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- alignment-handbook
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- trl
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- dpo
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- generated_from_trainer
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datasets:
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- HuggingFaceH4/ultrafeedback_binarized
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language:
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- zho
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- eng
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- fra
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- spa
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- por
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- deu
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- ita
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- rus
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- jpn
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- kor
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- vie
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- tha
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- ara
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model-index:
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- name: lambda-qwen2.5-14b-dpo-test
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# lambda-qwen2.5-14b-dpo-test
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This model is a fine-tuned version of [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct) on the HuggingFaceH4/ultrafeedback_binarized dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4919
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- Rewards/chosen: -2.4745
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- Rewards/rejected: -3.3729
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- Rewards/accuracies: 0.7400
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- Rewards/margins: 0.8984
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- Logps/rejected: -832.0724
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- Logps/chosen: -737.5234
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- Logits/rejected: -1.2739
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- Logits/chosen: -1.2560
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-07
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 128
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- total_eval_batch_size: 16
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
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| 0.5269 | 0.2094 | 100 | 0.5333 | -1.6756 | -2.3320 | 0.7000 | 0.6564 | -727.9815 | -657.6356 | -1.3952 | -1.3850 |
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| 0.5086 | 0.4187 | 200 | 0.5044 | -2.0906 | -2.9287 | 0.7040 | 0.8381 | -787.6511 | -699.1298 | -1.2939 | -1.2773 |
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| 0.4787 | 0.6281 | 300 | 0.4948 | -2.2927 | -3.1689 | 0.7320 | 0.8762 | -811.6696 | -719.3386 | -1.2846 | -1.2646 |
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| 0.4825 | 0.8375 | 400 | 0.4924 | -2.4470 | -3.3410 | 0.7400 | 0.8939 | -828.8748 | -734.7765 | -1.2644 | -1.2477 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.4.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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