Qwen2-5-Coder-32B-sft-3000-agent-diverse-real-5ep-5e-6
This model is a fine-tuned version of Qwen/Qwen2.5-Coder-32B-Instruct on the tb3000_agent_diverse_real 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: 5e-06
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 64
- optimizer: Use 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_ratio: 0.1
- num_epochs: 5
Training results
Framework versions
- Transformers 4.55.0
- Pytorch 2.8.0a0+gitd06a406
- Datasets 4.0.0
- Tokenizers 0.21.4
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Model tree for yuzhounie/sft_qwen32b
Base model
Qwen/Qwen2.5-32B Finetuned
Qwen/Qwen2.5-Coder-32B Finetuned
Qwen/Qwen2.5-Coder-32B-Instruct