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es-finetuned-squad-qa-minilmv2-16 – AI Model by subhasisj | AlphaNeural AI
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subhasisj
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es-finetuned-squad-qa-minilmv2-16
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transformers
pytorch
tensorboard
bert
question-answering
generated_from_trainer
endpoints_compatible
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es-finetuned-squad-qa-minilmv2-16
This model is a fine-tuned version of
subhasisj/es-TAPT-MLM-MiniLM
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.2304
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: 3e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
3.485
1.0
711
1.7377
1.6984
2.0
1422
1.3005
1.0772
3.0
2133
1.2348
0.9997
4.0
2844
1.2231
0.8976
5.0
3555
1.2304
Framework versions
Transformers 4.18.0
Pytorch 1.11.0+cu113
Datasets 2.2.1
Tokenizers 0.12.1
