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minilm-l12-h384-sst2-distilled – AI Model by philschmid | AlphaNeural AI
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philschmid
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minilm-l12-h384-sst2-distilled
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transformers
pytorch
tensorboard
roberta
text-classification
generated_from_trainer
glue
model-index
autotrain_compatible
endpoints_compatible
us
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minilm-l12-h384-sst2-distilled
This model is a fine-tuned version of
nreimers/MiniLMv2-L12-H384-distilled-from-RoBERTa-Large
on the glue dataset. It achieves the following results on the evaluation set:
Loss: 0.5417
Accuracy: 0.9220
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: 0.0001400785945474408
train_batch_size: 512
eval_batch_size: 512
seed: 33
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
2.2689
1.0
132
0.7102
0.8979
0.8295
2.0
264
0.5669
0.9117
0.5059
3.0
396
0.5545
0.9220
0.3722
4.0
528
0.5378
0.9209
0.2924
5.0
660
0.5417
0.9220
Framework versions
Transformers 4.17.0
Pytorch 1.10.2+cu113
Datasets 1.18.4
Tokenizers 0.11.6
