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indic-gpt – AI Model by NareshSandrugu | AlphaNeural AI
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NareshSandrugu
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indic-gpt
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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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indic-gpt
This model is a fine-tuned version of
gpt2
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 2.2759
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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 1000
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
5.7117
0.13
100
4.2005
3.6363
0.25
200
3.2403
3.091
0.38
300
2.7889
2.7788
0.51
400
2.5699
2.5997
0.64
500
2.4369
2.5141
0.76
600
2.3491
2.4268
0.89
700
2.2759
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.0
Tokenizers 0.15.0
