70B_4bit
This model is a fine-tuned version of unsloth/Llama-3.3-70B-Instruct on the wisenut_lora_sft 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-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 256
- total_eval_batch_size: 32
- optimizer: Use 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_steps: 20
- num_epochs: 1.0
Training results
Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.2.2
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for wisenut-nlp-team/Wisenut-3.3-70B-Instruct-4Bit-Lora-SFT
Base model
meta-llama/Llama-3.1-70B
Finetuned
meta-llama/Llama-3.3-70B-Instruct
Finetuned
unsloth/Llama-3.3-70B-Instruct