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reuters-gpt2-text-gen – AI Model by Dineshsoudagar | AlphaNeural AI
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Dineshsoudagar
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reuters-gpt2-text-gen
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transformers
tensorboard
safetensors
gpt2
text-generation
generated_from_trainer
Dineshsoudagar/reuters-gpt2-text-gen
finetune
mit
autotrain_compatible
text-generation-inference
endpoints_compatible
us
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reuters-gpt2-text-gen
This model is a fine-tuned version of
100daggers/reuters-gpt2-text-gen
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 3.9508
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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
4.2626
0.9987
286
4.4727
3.7809
1.9974
572
4.2128
3.5797
2.9996
859
4.0473
3.2899
3.9983
1145
3.9684
3.2056
4.9935
1430
3.9508
Framework versions
Transformers 4.44.1
Pytorch 2.0.1
Datasets 2.21.0
Tokenizers 0.19.1
