76 lines
2.3 KiB
Markdown
76 lines
2.3 KiB
Markdown
---
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library_name: transformers
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license: other
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base_model: Qwen/Qwen2.5-7B-Instruct
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tags:
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- llama-factory
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- full
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- generated_from_trainer
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model-index:
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- name: dpo_v16
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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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# dpo_v16
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This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the dpo_mcts_rag_v8 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8564
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- Rewards/chosen: 1.0146
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- Rewards/rejected: -0.5767
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- Rewards/accuracies: 0.6204
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- Rewards/margins: 1.5913
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- Logps/chosen: -65.8051
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- Logps/rejected: -74.8917
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- Logits/chosen: -0.5108
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- Logits/rejected: -0.5206
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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: 1e-06
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 3
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 12
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- total_eval_batch_size: 3
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.2
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- num_epochs: 1.0
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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/chosen | Logps/rejected | Logits/chosen | Logits/rejected |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:------------:|:--------------:|:-------------:|:---------------:|
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| 0.9257 | 0.4352 | 500 | 0.9691 | 1.0721 | -0.2211 | 0.6171 | 1.2933 | -65.6133 | -73.7064 | -0.5575 | -0.5659 |
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| 0.7847 | 0.8703 | 1000 | 0.8689 | 0.7341 | -0.9130 | 0.6223 | 1.6471 | -66.7400 | -76.0126 | -0.5218 | -0.5319 |
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### Framework versions
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- Transformers 4.49.0
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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