tp-csa-analyst-100k-final
This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the None 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 600
Training results
Framework versions
- PEFT 0.13.2
- Transformers 5.0.1.dev0
- Pytorch 2.8.0+cu126
- Datasets 3.2.0
- Tokenizers 0.22.2
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