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--- |
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base_model: JunxiongWang/mamba_0_75_sft |
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tags: |
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- alignment-handbook |
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- generated_from_trainer |
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datasets: |
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- HuggingFaceH4/ultrafeedback_binarized |
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model-index: |
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- name: mamba_0_75_dpo_ep3 |
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results: [] |
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--- |
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Please check [here](https://github.com/jxiw/MambaInLlama/tree/main) for details. |
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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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# mamba_0_75_dpo_ep3 |
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This model is a fine-tuned version of [JunxiongWang/mamba_0_75_sft](https://huggingface.co/JunxiongWang/mamba_0_75_sft) on the HuggingFaceH4/ultrafeedback_binarized dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7077 |
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- Rewards/chosen: -4.3611 |
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- Rewards/rejected: -7.0013 |
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- Rewards/accuracies: 0.7812 |
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- Rewards/margins: 2.6403 |
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- Logps/rejected: -333.1784 |
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- Logps/chosen: -302.4903 |
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- Logits/rejected: -2.8351 |
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- Logits/chosen: -2.8752 |
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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: 4 |
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- eval_batch_size: 8 |
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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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- total_train_batch_size: 32 |
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- total_eval_batch_size: 64 |
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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: 3 |
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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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| 0.1188 | 1.0466 | 2000 | 0.5385 | -1.3137 | -2.8323 | 0.7852 | 1.5186 | -291.4879 | -272.0161 | -2.9057 | -2.9472 | |
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| 0.0093 | 2.0931 | 4000 | 0.7077 | -4.3611 | -7.0013 | 0.7812 | 2.6403 | -333.1784 | -302.4903 | -2.8351 | -2.8752 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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