README.md

metadata

tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
model-index:
  - name: bnb-sentiment-model-saagie
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: emotion
          type: emotion
          args: split
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.93

bnb-sentiment-model-saagie

This model is a fine-tuned version of j-hartmann/emotion-english-distilroberta-base on the emotion dataset. It achieves the following results on the evaluation set:

• Loss: 0.2269
• Accuracy: 0.93

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

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3839	1.0	1500	0.2857	0.9333
0.1902	2.0	3000	0.2143	0.9417
0.1159	3.0	4500	0.2269	0.93

Framework versions

• Transformers 4.18.0
• Pytorch 1.8.1
• Datasets 2.12.0
• Tokenizers 0.12.1