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BQTrans-new-cont – AI Model by SKNahin | AlphaNeural AI
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SKNahin
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BQTrans-new-cont
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transformers
safetensors
qwen2
text-generation
llama-factory
full
generated_from_trainer
conversational
SKNahin/BQTrans-new
finetune
autotrain_compatible
text-generation-inference
endpoints_compatible
us
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BQTrans-new-cont
This model is a fine-tuned version of
SKNahin/BQTrans-new
on the sample_1 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: 10
eval_batch_size: 8
seed: 555
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 10
total_train_batch_size: 200
total_eval_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: constant
lr_scheduler_warmup_steps: 50
num_epochs: 5
Training results
Framework versions
Transformers 4.49.0
Pytorch 2.6.0+cu124
Datasets 3.2.0
Tokenizers 0.21.0
