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---
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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: 2and3_apps_30k_v6
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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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# 2and3_apps_30k_v6
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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 2and3_apps_30k_v6 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1593
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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: 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: 4
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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: 4
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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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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 0.1754 | 0.1025 | 100 | 0.1826 |
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| 0.1914 | 0.2049 | 200 | 0.1759 |
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| 0.1891 | 0.3074 | 300 | 0.1709 |
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| 0.1999 | 0.4098 | 400 | 0.1681 |
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| 0.1822 | 0.5123 | 500 | 0.1657 |
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| 0.1815 | 0.6148 | 600 | 0.1631 |
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| 0.1823 | 0.7172 | 700 | 0.1616 |
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| 0.1693 | 0.8197 | 800 | 0.1603 |
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| 0.1789 | 0.9221 | 900 | 0.1596 |
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### Framework versions
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- Transformers 4.46.1
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- Pytorch 2.6.0+cu124
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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