should probably proofread and complete it, then remove this comment. -->
1
3 commits
1 linked in READMEs
updated Jun 28, 2026
README
OmniCoT-R1
This model is a fine-tuned version of Qwen/Qwen2.5-VL-7B-Instruct on OmniCoT-related panoramic CoT data.
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-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- total_eval_batch_size: 16
- 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: 3.0
Training results
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.0.0
- Tokenizers 0.22.1
conversational
endpoints_compatible
full
generated_from_trainer
image-text-to-text
llama-factory
qwen2_5_vl
safetensors
text-generation-inference
transformers
should probably proofread and complete it, then remove this comment. -->
1
3 commits
1 linked in READMEs
updated Jun 28, 2026
README
OmniCoT-R1
This model is a fine-tuned version of Qwen/Qwen2.5-VL-7B-Instruct on OmniCoT-related panoramic CoT data.
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-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- total_eval_batch_size: 16
- 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: 3.0
Training results
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.0.0
- Tokenizers 0.22.1
conversational
endpoints_compatible
full
generated_from_trainer
image-text-to-text
llama-factory
qwen2_5_vl
safetensors
text-generation-inference
transformers