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distilbert_sa_GLUE_Experiment_logit_kd_wnli_256 – AI Model by gokuls | AlphaNeural AI
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distilbert_sa_GLUE_Experiment_logit_kd_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_logit_kd_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: 0.3436
Accuracy: 0.5634
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
Validation Loss
Accuracy
0.3511
1.0
3
0.3436
0.5634
0.3479
2.0
6
0.3457
0.5634
0.3474
3.0
9
0.3462
0.5634
0.3477
4.0
12
0.3442
0.5634
0.3486
5.0
15
0.3442
0.5634
0.3479
6.0
18
0.3455
0.5634
Framework versions
Transformers 4.26.0
Pytorch 1.14.0a0+410ce96
Datasets 2.9.0
Tokenizers 0.13.2
