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gdn-300M-v5-gdn – AI Model by deqing | AlphaNeural AI
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gdn-300M-v5-gdn
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transformers
safetensors
gated_deltanet
text-generation
generated_from_trainer
endpoints_compatible
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gdn-300M-v5-gdn
This model is a fine-tuned version of
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 2.9694
Num Input Tokens Seen: 9437184000
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: 0.0003
train_batch_size: 32
eval_batch_size: 32
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 8
total_train_batch_size: 512
total_eval_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 500
num_epochs: 1
Training results
Framework versions
Transformers 5.3.0
Pytorch 2.10.0+cu128
Datasets 4.7.0
Tokenizers 0.22.2
