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strict-small-2 – AI Model by hopkins | AlphaNeural AI
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hopkins
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strict-small-2
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transformers
pytorch
tensorboard
gpt2
text-generation
generated_from_trainer
generator
mit
autotrain_compatible
text-generation-inference
endpoints_compatible
us
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strict-small-2
This model is a fine-tuned version of
gpt2
on the generator dataset. It achieves the following results on the evaluation set:
Loss: 5.8423
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: 128
eval_batch_size: 128
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 1024
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 1000
num_epochs: 50
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
4.1594
7.33
2000
3.8824
2.8132
14.65
4000
4.2196
2.121
21.98
6000
4.7343
1.6016
29.3
8000
5.2934
1.2441
36.63
10000
5.6547
1.0171
43.96
12000
5.8423
Framework versions
Transformers 4.25.1
Pytorch 1.13.1+cu117
Datasets 2.8.0
Tokenizers 0.13.2
