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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: agenttuning_v4_15k_tag4
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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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# agenttuning_v4_15k_tag4
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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 agenttuning_v4_15k_tag4 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3463
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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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- total_train_batch_size: 4
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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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| 0.411 | 0.0272 | 100 | 0.4573 |
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| 0.4154 | 0.0544 | 200 | 0.4534 |
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| 0.45 | 0.0816 | 300 | 0.4339 |
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| 0.4442 | 0.1088 | 400 | 0.4359 |
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| 0.5011 | 0.1361 | 500 | 0.4093 |
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| 0.4743 | 0.1633 | 600 | 0.4134 |
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| 0.2855 | 0.1905 | 700 | 0.4042 |
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| 0.3281 | 0.2177 | 800 | 0.4117 |
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| 0.3854 | 0.2449 | 900 | 0.4114 |
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| 0.5613 | 0.2721 | 1000 | 0.4117 |
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| 0.5624 | 0.2993 | 1100 | 0.4049 |
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| 0.4616 | 0.3265 | 1200 | 0.3989 |
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| 0.373 | 0.3537 | 1300 | 0.3982 |
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| 0.5473 | 0.3810 | 1400 | 0.3963 |
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| 0.5104 | 0.4082 | 1500 | 0.3924 |
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| 0.4531 | 0.4354 | 1600 | 0.3852 |
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| 0.3872 | 0.4626 | 1700 | 0.3814 |
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| 0.4966 | 0.4898 | 1800 | 0.3819 |
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| 0.5067 | 0.5170 | 1900 | 0.3738 |
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| 0.4067 | 0.5442 | 2000 | 0.3749 |
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| 0.3464 | 0.5714 | 2100 | 0.3786 |
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| 0.353 | 0.5986 | 2200 | 0.3678 |
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| 0.4483 | 0.6259 | 2300 | 0.3640 |
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| 0.3288 | 0.6531 | 2400 | 0.3594 |
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| 0.4155 | 0.6803 | 2500 | 0.3576 |
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| 0.3656 | 0.7075 | 2600 | 0.3538 |
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| 0.303 | 0.7347 | 2700 | 0.3544 |
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| 0.4023 | 0.7619 | 2800 | 0.3527 |
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| 0.3726 | 0.7891 | 2900 | 0.3503 |
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| 0.3333 | 0.8163 | 3000 | 0.3487 |
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| 0.4189 | 0.8435 | 3100 | 0.3462 |
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| 0.3927 | 0.8707 | 3200 | 0.3452 |
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| 0.3778 | 0.8980 | 3300 | 0.3466 |
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| 0.3443 | 0.9252 | 3400 | 0.3466 |
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| 0.3868 | 0.9524 | 3500 | 0.3470 |
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| 0.382 | 0.9796 | 3600 | 0.3463 |
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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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