README.md

metadata

license: mit
base_model: microsoft/MiniLM-L12-H384-uncased
tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - f1
model-index:
  - name: test01
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: emotion
          type: emotion
          config: split
          split: validation
          args: split
        metrics:
          - name: F1
            type: f1
            value: 0.9104824364647098

test01

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: 0.3902
• F1: 0.9105

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

Training results

Training Loss	Epoch	Step	Validation Loss	F1
1.4186	1.0	250	1.1125	0.4765
0.9485	2.0	500	0.7212	0.8291
0.6309	3.0	750	0.5014	0.8881
0.4772	4.0	1000	0.4186	0.9122
0.4078	5.0	1250	0.3902	0.9105

Framework versions

• Transformers 4.33.2
• Pytorch 2.0.1+cu117
• Datasets 2.14.5
• Tokenizers 0.13.3