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RM-harmless_harmless_contrast_loraR64_20000_gemma2b_lr5e-06_bs2_g4 – AI Model by Holarissun | AlphaNeural AI
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Holarissun
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RM-harmless_harmless_contrast_loraR64_20000_gemma2b_lr5e-06_bs2_g4
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peft
safetensors
trl
reward-trainer
generated_from_trainer
google/gemma-2b
adapter
gemma
us
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RM-harmless_harmless_contrast_loraR64_20000_gemma2b_lr5e-06_bs2_g4
This model is a fine-tuned version of
google/gemma-2b
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1054
Accuracy: 0.961
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: 5e-06
train_batch_size: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.1443
1.0
2250
0.1540
0.942
0.0906
2.0
4500
0.1054
0.961
Framework versions
PEFT 0.10.0
Transformers 4.40.1
Pytorch 2.1.2+cu121
Datasets 2.18.0
Tokenizers 0.19.1
