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README.md
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license: mit
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---
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license: mit
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---
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# 0428
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This model is a fine-tuned version of [../../models/Qwen1.5-7B-sft-0425](https://huggingface.co/../../models/Qwen1.5-7B-sft-0425) on the alpaca_formatted_review_new_data_greater_7 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0733
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## Model description
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Qwen1.5 is the beta version of Qwen2, a transformer-based decoder-only language model pretrained on a large amount of data. In comparison with the previous released Qwen, the improvements include:
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* 8 model sizes, including 0.5B, 1.8B, 4B, 7B, 14B, 32B and 72B dense models, and an MoE model of 14B with 2.7B activated;
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* Significant performance improvement in Chat models;
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* Multilingual support of both base and chat models;
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* Stable support of 32K context length for models of all sizes
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* No need of `trust_remote_code`.
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For more details, please refer to the [blog post](https://qwenlm.github.io/blog/qwen1.5/) and [GitHub repo](https://github.com/QwenLM/Qwen1.5).
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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: 2
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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: 2
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 8
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- total_eval_batch_size: 2
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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_steps: 5
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- num_epochs: 5.0
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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| :-----------: | :---: | :--: | :-------------: |
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| 0.8554 | 0.25 | 10 | 1.1541 |
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| 0.6139 | 0.5 | 20 | 1.1258 |
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| 0.629 | 0.75 | 30 | 1.1057 |
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| 0.7943 | 1.0 | 40 | 1.0993 |
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| 0.6658 | 1.25 | 50 | 1.0964 |
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| 0.778 | 1.5 | 60 | 1.0892 |
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| 0.593 | 1.75 | 70 | 1.0868 |
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| 0.8847 | 2.0 | 80 | 1.0816 |
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| 0.5067 | 2.25 | 90 | 1.0806 |
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| 0.9706 | 2.5 | 100 | 1.0789 |
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| 0.7302 | 2.75 | 110 | 1.0763 |
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| 0.6855 | 3.0 | 120 | 1.0768 |
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| 0.4358 | 3.25 | 130 | 1.0754 |
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| 0.5777 | 3.5 | 140 | 1.0740 |
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| 0.5687 | 3.75 | 150 | 1.0732 |
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| 0.6462 | 4.0 | 160 | 1.0732 |
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| 0.5465 | 4.25 | 170 | 1.0733 |
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| 0.7926 | 4.5 | 180 | 1.0737 |
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| 0.4968 | 4.75 | 190 | 1.0735 |
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| 0.6406 | 5.0 | 200 | 1.0733 |
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### Framework versions
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- PEFT 0.10.0
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- Transformers 4.40.0
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- Pytorch 2.1.0+cu121
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- Datasets 2.14.5
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- Tokenizers 0.19.1
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