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adapters – AI Model by c-mohanraj | AlphaNeural AI
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c-mohanraj
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adapters
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peft
safetensors
adapter
lora
sft
transformers
trl
text-generation
conversational
google/gemma-3-27b-it
gemma
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adapters
This model is a fine-tuned version of
google/gemma-3-27b-it
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1753
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: 0.0002
train_batch_size: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
1.6826
0.7529
200
0.2053
1.3485
1.5045
400
0.1804
1.082
2.2560
600
0.1753
Framework versions
PEFT 0.17.1
Transformers 4.56.2
Pytorch 2.6.0+cu124
Datasets 4.1.1
Tokenizers 0.22.1
