README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
base_model: gpt2
model-index:
  - name: jq_emo_gpt
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: emotion
          type: emotion
          config: split
          split: validation
          args: split
        metrics:
          - type: accuracy
            value: 0.947
            name: Accuracy

jq_emo_gpt

This model is a fine-tuned version of gpt2 on the emotion dataset. It achieves the following results on the evaluation set:

• Loss: 0.2536
• Accuracy: 0.947

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: 6400
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5109	1.0	16000	0.5014	0.929
0.3765	2.0	32000	0.3135	0.9385
0.2526	3.0	48000	0.2385	0.945
0.1952	4.0	64000	0.2536	0.947

Framework versions

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