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--- |
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library_name: transformers |
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license: other |
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base_model: hon9kon9ize/CantoneseLLM-7B-sft |
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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: CantoneseLLMChat-v1.0 |
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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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# CantoneseLLMChat-v1.0 |
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This model is a fine-tuned version of [hon9kon9ize/CantoneseLLM-7B-sft](https://huggingface.co/hon9kon9ize/CantoneseLLM-7B-sft) on the dpo_v1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3170 |
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- Rewards/chosen: -0.7307 |
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- Rewards/rejected: -3.1239 |
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- Rewards/accuracies: 0.8464 |
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- Rewards/margins: 2.3931 |
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- Logps/rejected: -226.0627 |
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- Logps/chosen: -191.7517 |
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- Logits/rejected: -1.5777 |
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- Logits/chosen: -1.5363 |
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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-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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: 3.0 |
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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/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.0835 | 1.3495 | 500 | 0.3282 | -0.6181 | -2.8043 | 0.8494 | 2.1862 | -222.8677 | -190.6253 | -1.5563 | -1.5215 | |
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| 0.1151 | 2.6991 | 1000 | 0.3186 | -0.7277 | -3.1230 | 0.8524 | 2.3953 | -226.0546 | -191.7211 | -1.5777 | -1.5363 | |
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### Framework versions |
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- Transformers 4.45.0 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.20.0 |
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