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HW2-reward – AI Model by KoNqUeRoR3891 | AlphaNeural AI
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KoNqUeRoR3891
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HW2-reward
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transformers
safetensors
gpt2
text-classification
trl
reward-trainer
generated_from_trainer
piqa
KoNqUeRoR3891/HW2-supervised
finetune
mit
model-index
autotrain_compatible
text-generation-inference
endpoints_compatible
us
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HW2-reward
This model is a fine-tuned version of
KoNqUeRoR3891/HW2-supervised
on the piqa dataset. It achieves the following results on the evaluation set:
Loss: 0.7024
Accuracy: 0.6408
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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.6793
1.0
3626
0.6733
0.5782
0.6767
2.0
7252
0.6590
0.6210
0.5686
3.0
10878
0.7024
0.6408
Framework versions
Transformers 4.44.2
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1
