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race-albert-v2 – AI Model by hannesvgel | AlphaNeural AI
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hannesvgel
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race-albert-v2
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transformers
safetensors
albert
multiple-choice
generated_from_trainer
ehovy/race
albert/albert-base-v2
finetune
apache-2.0
endpoints_compatible
us
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race-albert-v2
This model is a fine-tuned version of
albert-base-v2
on the
race dataset(middle)
. It achieves the following results on the test set:
Loss: 0.8710
Accuracy: 0.7089
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: 2e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 4
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.8709
1.0
3178
0.8257
0.6769
0.6377
2.0
6356
0.8329
0.7152
0.3548
3.0
9534
1.0367
0.7124
0.1412
4.0
12712
1.5380
0.7145
Framework versions
Transformers 4.52.2
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1
