eth-sri
kodcode-v1-qwen36
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README
License: otherModel 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: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 6
- total_train_batch_size: 48
- total_eval_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 3
Training results
Framework versions
- Transformers 5.6.0
- Pytorch 2.12.0+cu130
- Datasets 4.0.0
- Tokenizers 0.22.2
Model provider
eth-sri
Model tree
Base
Qwen/Qwen3.6-27B
Fine-tuned
this model
Modalities
Input
Video, Text, Image
Output
Text
Pricing
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Model APIs
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Container
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