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sequential-training – AI Model by VamsiPranav | AlphaNeural AI
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sequential-training
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transformers
tensorboard
safetensors
gpt2
text-generation
generated_from_trainer
openai-community/gpt2
finetune
mit
autotrain_compatible
text-generation-inference
endpoints_compatible
us
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sequential-training
This model is a fine-tuned version of
gpt2
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: 0.0005
train_batch_size: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 512
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 1000
num_epochs: 100
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0
