This model is a fine-tuned version of microsoft/MiniLM-L12-H384-uncased on the emotion dataset. It achieves the following results on the evaluation set:

Loss: 0.1918
F1: 0.9323

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: 2e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1
1.3627	1.0	250	1.0048	0.5936
0.8406	2.0	500	0.6477	0.8608
0.5344	3.0	750	0.4025	0.9099
0.3619	4.0	1000	0.3142	0.9188
0.274	5.0	1250	0.2489	0.9277
0.2225	6.0	1500	0.2320	0.9303
0.191	7.0	1750	0.2083	0.9298
0.1731	8.0	2000	0.1969	0.9334
0.1606	9.0	2250	0.1928	0.9362
0.1462	10.0	2500	0.1918	0.9323

Framework versions

Transformers 4.15.0
Pytorch 1.10.0+cu111
Datasets 1.17.0
Tokenizers 0.10.3

nickmuchi/minilm-finetuned-emotion_nm

minilm-finetuned-emotion_nm

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

nickmuchi/
minilm-finetuned-emotion_nm