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sdar_4b_trace_sft-final – AI Model by autoprogrammer | AlphaNeural AI
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sdar_4b_trace_sft-final
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transformers
safetensors
sdar
feature-extraction
llama-factory
full
generated_from_trainer
custom_code
JetLM/SDAR-4B-Chat
finetune
other
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sft
This model is a fine-tuned version of
./training/model/SDAR-4B-Chat
on an unknown 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: 1e-05
train_batch_size: 4
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 2
total_train_batch_size: 64
total_eval_batch_size: 64
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: 0.03
num_epochs: 3.0
Training results
Framework versions
Transformers 4.52.4
Pytorch 2.8.0+cu128
Datasets 3.6.0
Tokenizers 0.21.1
