README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
model-index:
  - name: twitter_emotions
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: emotion
          type: emotion
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9375

twitter_emotions

This model is a fine-tuned version of sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 on the emotion dataset. It achieves the following results on the evaluation set:

• Loss: 0.1647
• Accuracy: 0.9375

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2486	1.0	2000	0.2115	0.931
0.135	2.0	4000	0.1725	0.936
0.1041	3.0	6000	0.1647	0.9375

Framework versions

• Transformers 4.12.5
• Pytorch 1.10.0+cu111
• Datasets 1.15.1
• Tokenizers 0.10.3