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distilbert_sa_GLUE_Experiment_data_aug_wnli_256 – AI Model by gokuls | AlphaNeural AI
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distilbert_sa_GLUE_Experiment_data_aug_wnli_256
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transformers
pytorch
tensorboard
distilbert
text-classification
generated_from_trainer
en
glue
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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distilbert_sa_GLUE_Experiment_data_aug_wnli_256
This model is a fine-tuned version of
distilbert-base-uncased
on the GLUE WNLI dataset. It achieves the following results on the evaluation set:
Loss: 1.5078
Accuracy: 0.1268
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: 256
eval_batch_size: 256
seed: 10
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 50
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Accuracy
Validation Loss
0.6609
1.0
218
0.1268
1.5078
0.5075
2.0
436
2.2234
0.0986
0.4251
3.0
654
3.1955
0.0986
0.3611
4.0
872
3.9830
0.0986
0.3174
5.0
1090
4.3550
0.0845
0.2856
6.0
1308
4.6227
0.0845
Framework versions
Transformers 4.26.0
Pytorch 1.14.0a0+410ce96
Datasets 2.9.0
Tokenizers 0.13.2
