metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - f1
model-index:
  - name: minilm-finetuned-emotion
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: emotion
          type: emotion
          args: default
        metrics:
          - name: F1
            type: f1
            value: 0.9117582218338629

minilm-finetuned-emotion

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: 0.3891
F1: 0.9118

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: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1
1.3957	1.0	250	1.0134	0.6088
0.8715	2.0	500	0.6892	0.8493
0.6085	3.0	750	0.4943	0.8920
0.4626	4.0	1000	0.4096	0.9078
0.3961	5.0	1250	0.3891	0.9118

Framework versions

Transformers 4.12.3
Pytorch 1.6.0
Datasets 1.15.1
Tokenizers 0.10.3