README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - tweet_eval
metrics:
  - f1
model-index:
  - name: emotion_trained_31415
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: tweet_eval
          type: tweet_eval
          args: emotion
        metrics:
          - name: F1
            type: f1
            value: 0.719757533529152

emotion_trained_31415

This model is a fine-tuned version of distilbert-base-uncased on the tweet_eval dataset. It achieves the following results on the evaluation set:

• Loss: 0.9274
• F1: 0.7198

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: 6.961635072722524e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 31415
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	204	0.6177	0.7137
No log	2.0	408	0.7489	0.6761
0.5082	3.0	612	0.8233	0.7283
0.5082	4.0	816	0.9274	0.7198

Framework versions

• Transformers 4.12.5
• Pytorch 1.9.1
• Datasets 1.16.1
• Tokenizers 0.10.3