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RM-TLDR_contrast_loraR64_-1_gemma2b_lr1.41e-05_bs2_g4 – AI Model by Holarissun | AlphaNeural AI
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Holarissun
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RM-TLDR_contrast_loraR64_-1_gemma2b_lr1.41e-05_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-TLDR_contrast_loraR64_-1_gemma2b_lr1.41e-05_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: 0.8155
Accuracy: 0.5776
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: 1.41e-05
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
0.0092
1.0
1548
0.7784
0.5838
0.0056
2.0
3096
0.8155
0.5776
Framework versions
PEFT 0.10.0
Transformers 4.38.2
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2
