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README.md
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---
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license: other
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base_model: Qwen1.5-0.5B
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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: train_2024-03-31-14-36-00-superzj
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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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# train_2024-03-31-14-36-00-superzj
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This model is a fine-tuned version of [Qwen1.5-0.5B](https://huggingface.co/
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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-05
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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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- gradient_accumulation_steps: 8
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- total_train_batch_size: 32
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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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- num_epochs: 10.0
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### Training results
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 1.13.1+cu116
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- Datasets 2.14.6
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- Tokenizers 0.15.2
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```
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全量微调,使用语料来自小说--重生之超级战舰
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Fully fine-tuned, using corpus from the novel - Rebirth of the Super Battleship
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```
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---
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license: other
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base_model: Qwen1.5-0.5B
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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: train_2024-03-31-14-36-00-superzj
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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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# train_2024-03-31-14-36-00-superzj
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This model is a fine-tuned version of [Qwen1.5-0.5B](https://huggingface.co/Terminator-of-AI/Qwen1.5-0.5B-finetuning-by-super-battleship) on the superzj dataset.
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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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+
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## Training and evaluation data
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+
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More information needed
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+
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## Training procedure
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+
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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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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- gradient_accumulation_steps: 8
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- total_train_batch_size: 32
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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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- num_epochs: 10.0
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### Training results
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+
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+
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+
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### Framework versions
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+
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- Transformers 4.38.2
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+
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- Pytorch 1.13.1+cu116
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+
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- Datasets 2.14.6
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- Tokenizers 0.15.2
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```
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全量微调,使用语料来自小说--重生之超级战舰
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+
Fully fine-tuned, using corpus from the novel - Rebirth of the Super Battleship
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```
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