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---
library_name: transformers
license: other
base_model: /data2/wuxinrui/RoboBrain2.0/HF_Models/BAAI-RoboBrain2.0-7B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: output_1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# output_1
This model is a fine-tuned version of [/data2/wuxinrui/RoboBrain2.0/HF_Models/BAAI-RoboBrain2.0-7B](https://huggingface.co//data2/wuxinrui/RoboBrain2.0/HF_Models/BAAI-RoboBrain2.0-7B) on the COT_1_shorten_shorten2_budgetthinker_abalation_mllm, the COT_1_shorten_budgetthinker_abalation_mllm, the COT_1_budgetthinker_abalation_mllm, the COT_2_shorten_shorten2_budgetthinker_abalation_mllm, the COT_2_shorten_budgetthinker_abalation_mllm, the COT_2_budgetthinker_abalation_mllm, the COT_3_shorten_shorten2_budgetthinker_abalation_mllm, the COT_3_shorten_budgetthinker_abalation_mllm, the COT_3_budgetthinker_abalation_mllm, the COT_4_shorten_shorten2_budgetthinker_abalation_mllm, the COT_4_shorten_budgetthinker_abalation_mllm, the COT_4_budgetthinker_abalation_mllm, the COT_5_shorten_shorten2_budgetthinker_abalation_mllm, the COT_5_shorten_budgetthinker_abalation_mllm, the COT_5_budgetthinker_abalation_mllm, the COT_6_shorten_shorten2_budgetthinker_abalation_mllm, the COT_6_shorten_budgetthinker_abalation_mllm, the COT_6_budgetthinker_abalation_mllm, the COT_8_shorten_shorten2_budgetthinker_abalation_mllm, the COT_8_shorten_budgetthinker_abalation_mllm, the COT_8_budgetthinker_abalation_mllm, the COT_9_shorten_shorten2_budgetthinker_abalation_mllm, the COT_9_shorten_budgetthinker_abalation_mllm, the COT_9_budgetthinker_abalation_mllm, the COT_10_shorten_shorten2_budgetthinker_abalation_mllm, the COT_10_shorten_budgetthinker_abalation_mllm and the COT_10_budgetthinker_abalation_mllm datasets.
## 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: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 6
- gradient_accumulation_steps: 2
- total_train_batch_size: 24
- total_eval_batch_size: 48
- optimizer: Use OptimizerNames.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: 2.0
### Training results
### Framework versions
- Transformers 4.51.3
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1
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