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PMCQ-Gemma2-9b – AI Model by Kamyar-zeinalipour | AlphaNeural AI
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Kamyar-zeinalipour
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PMCQ-Gemma2-9b
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peft
tensorboard
safetensors
trl
sft
generated_from_trainer
google/gemma-2-9b-it
adapter
gemma
us
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Model card
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gemma2_9b_LORA_Persian_MCQ_16_32_v1
This model is a fine-tuned version of
google/gemma-2-9b-it
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.8247
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: 0.0001
train_batch_size: 4
eval_batch_size: 4
seed: 100
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 4
total_train_batch_size: 32
total_eval_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
1.1752
1.0
375
1.1416
0.8005
2.0
750
0.9006
0.6332
3.0
1125
0.8247
Framework versions
PEFT 0.12.1.dev0
Transformers 4.44.0.dev0
Pytorch 2.1.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
