deberta-v3-xsmall-emotion
This model is a fine-tuned version of
microsoft/deberta-v3-xsmall
on the emotion dataset.
It achieves the following results on the evaluation set:
-
Loss: 0.1877
-
Accuracy: 0.932
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
-
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
|
|
1.3683
|
1.0
|
500
|
0.8479
|
0.6975
|
|
0.547
|
2.0
|
1000
|
0.2881
|
0.905
|
|
0.2378
|
3.0
|
1500
|
0.2116
|
0.925
|
|
0.1704
|
4.0
|
2000
|
0.1877
|
0.932
|
|
0.1392
|
5.0
|
2500
|
0.1718
|
0.9295
|
Framework versions
-
Transformers 4.12.3
-
Pytorch 1.9.1
-
Datasets 1.15.1
-
Tokenizers 0.10.3