sft
This model is a fine-tuned version of Qwen/Qwen2.5-7B on the finetune_bitcoin_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.6746
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-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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: 3.0
- mixed_precision_training: Native AMP
Training results
Framework versions
- PEFT 0.15.0
- Transformers 4.51.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.0
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Model tree for crypto-lab/qwen25-7b-bitcoin-lora
Base model
Qwen/Qwen2.5-7B