README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - go_emotions
metrics:
  - f1
  - accuracy
model-index:
  - name: go_emo_gpt
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: go_emotions
          type: go_emotions
          config: simplified
          split: validation
          args: simplified
        metrics:
          - name: F1
            type: f1
            value: 0.5928384279475983
          - name: Accuracy
            type: accuracy
            value: 0.49428676741614447

go_emo_gpt

This model is a fine-tuned version of distilgpt2 on the go_emotions dataset. It achieves the following results on the evaluation set:

• Loss: 0.0978
• F1: 0.5928
• Roc Auc: 0.7602
• Accuracy: 0.4943

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: 1e-05
• train_batch_size: 1
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: (13023,)
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.1086	1.0	43410	0.0993	0.5690	0.7444	0.4740
0.1003	2.0	86820	0.0969	0.5885	0.7552	0.4893
0.0858	3.0	130230	0.0978	0.5928	0.7602	0.4943

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu117
• Datasets 2.12.0
• Tokenizers 0.13.3