Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
MiniLMv2-L6-H384-sst2 – AI Model by philschmid | AlphaNeural AI
You can deploy this model and start earning money today!
philschmid
/
MiniLMv2-L6-H384-sst2
like
0
transformers
pytorch
tensorboard
roberta
text-classification
generated_from_trainer
glue
model-index
autotrain_compatible
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
MiniLMv2-L6-H384-sst2
This model is a fine-tuned version of
nreimers/MiniLMv2-L6-H384-distilled-from-RoBERTa-Large
on the glue dataset. It achieves the following results on the evaluation set:
Loss: 0.2532
Accuracy: 0.9197
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: 32
eval_batch_size: 32
seed: 42
distributed_type: sagemaker_data_parallel
num_devices: 8
total_train_batch_size: 256
total_eval_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.5787
1.0
264
0.3496
0.8624
0.3413
2.0
528
0.2599
0.8991
0.2716
3.0
792
0.2651
0.9048
0.2343
4.0
1056
0.2532
0.9197
0.2165
5.0
1320
0.2636
0.9151
Framework versions
Transformers 4.17.0
Pytorch 1.10.2+cu113
Datasets 1.18.4
Tokenizers 0.11.6
