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Model: mlfoundations-cua-dev/qwen2_5vl_7b_easyr1_10k_hard_segui3b_easy_gta1-4MP
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---
library_name: transformers
license: other
base_model: Qwen/Qwen2.5-VL-7B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: qwen2_5vl_7b_easyr1_10k_hard_segui3b_easy_gta1-4MP_lr_1_0e-06_bs_1_epochs_1.0_max_pixels_4000000_deepspeed
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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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
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.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-06
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
### Training results
### Framework versions
- Transformers 4.52.4
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1