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albert-base-v2-finetuned-squad-v2 – AI Model by BaoKien | AlphaNeural AI
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BaoKien
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albert-base-v2-finetuned-squad-v2
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transformers
pytorch
tensorboard
albert
question-answering
generated_from_trainer
squad_v2
apache-2.0
endpoints_compatible
us
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albert-base-v2-finetuned-squad-v2
This model is a fine-tuned version of
albert-base-v2
on the squad_v2 dataset. It achieves the following results on the evaluation set:
Loss: 0.9645
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: 16
eval_batch_size: 16
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
0.864
1.0
8248
0.8698
0.6246
2.0
16496
0.8351
0.4359
3.0
24744
0.9645
Performance
'exact': 78.36267160784975,
'f1': 81.72483834090231,
'total': 11873,
'HasAns_exact': 74.527665317139,
'HasAns_f1': 81.26164062441536,
'HasAns_total': 5928,
'NoAns_exact': 82.18671152228764,
'NoAns_f1': 82.18671152228764,
'NoAns_total': 5945,
'best_exact': 78.36267160784975,
'best_exact_thresh': 0.9990501403808594,
'best_f1': 81.72483834090268,
'best_f1_thresh': 0.9990501403808594,
'total_time_in_seconds': 224.37217425400013,
'samples_per_second': 52.9165438605555,
'latency_in_seconds': 0.018897681651983505
Framework versions
Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3
