sft_graph
This model is a fine-tuned version of Qwen/Qwen2.5-1.5B-Instruct on the asynchow_graph_code_minutes dataset. It achieves the following results on the evaluation set:
- Loss: 0.1931
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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- 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_ratio: 0.05
- num_epochs: 2.0
Training results
Framework versions
- Transformers 4.57.6
- Pytorch 2.11.0+cu130
- Datasets 4.0.0
- Tokenizers 0.22.2