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Model: mlfoundations-cua-dev/qwen2_5vl_7b_easyr1_10k_hard_segui3b_easy_gta1-4MP Source: Original Platform
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README.md
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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-VL-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: qwen2_5vl_7b_easyr1_10k_hard_segui3b_easy_gta1-4MP_lr_1_0e-06_bs_1_epochs_1.0_max_pixels_4000000_deepspeed
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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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# qwen2_5vl_7b_easyr1_10k_hard_segui3b_easy_gta1-4MP_lr_1_0e-06_bs_1_epochs_1.0_max_pixels_4000000_deepspeed
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This model is a fine-tuned version of [Qwen/Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct) on the easyr1-10k-hard-segui3b-easy-gta1-4MP 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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## 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: 1e-06
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- train_batch_size: 1
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- total_train_batch_size: 8
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- total_eval_batch_size: 64
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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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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 1.0
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### Training results
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### Framework versions
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- Transformers 4.52.4
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- Pytorch 2.7.1+cu126
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- Datasets 3.6.0
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- Tokenizers 0.21.1
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