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reward_model_anthropic – AI Model by shubhamgantayat | AlphaNeural AI
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reward_model_anthropic
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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reward_model_anthropic
This model is a fine-tuned version of
google-bert/bert-base-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.7057
Accuracy: 0.5144
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-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.703
1.0
625
0.6963
0.5062
0.7034
2.0
1250
0.6919
0.5236
0.6978
3.0
1875
0.7057
0.5144
Framework versions
Transformers 4.38.2
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2
