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deberta-reward-model – AI Model by cheonkamjeong | AlphaNeural AI
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deberta-reward-model
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transformers
tensorboard
safetensors
deberta-v2
text-classification
trl
reward-trainer
generated_from_trainer
microsoft/deberta-v3-large
finetune
mit
autotrain_compatible
endpoints_compatible
us
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deberta-reward-model
This model is a fine-tuned version of
microsoft/deberta-v3-large
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0095
Accuracy: 0.995
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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.0433
2.0
100
0.0274
0.9875
0.0017
4.0
200
0.0105
0.995
0.0001
6.0
300
0.0095
0.995
0.0001
8.0
400
0.0090
0.995
0.0002
10.0
500
0.0095
0.995
Framework versions
Transformers 4.45.1
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.20.0
