metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - tweet_eval
metrics:
  - f1
base_model: distilbert-base-uncased
model-index:
  - name: demo_emotion_42
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: tweet_eval
          type: tweet_eval
          args: emotion
        metrics:
          - type: f1
            value: 0.7348035780583043
            name: F1

demo_emotion_42

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: 0.9818
F1: 0.7348

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: 7.551070618629693e-05
train_batch_size: 16
eval_batch_size: 16
seed: 0
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	0.7431	0.6530
No log	2.0	408	0.6943	0.7333
0.5176	3.0	612	0.8456	0.7326
0.5176	4.0	816	0.9818	0.7348

Framework versions

Transformers 4.12.5
Pytorch 1.9.1
Datasets 1.16.1
Tokenizers 0.10.3