metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - tweet_eval
metrics:
  - accuracy
  - f1
model-index:
  - name: tiny-mlm-tweet-target-tweet
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: tweet_eval
          type: tweet_eval
          config: emotion
          split: train
          args: emotion
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7165775401069518
          - name: F1
            type: f1
            value: 0.7162540037184906

tiny-mlm-tweet-target-tweet

This model is a fine-tuned version of muhtasham/tiny-mlm-tweet on the tweet_eval dataset. It achieves the following results on the evaluation set:

Loss: 1.2643
Accuracy: 0.7166
F1: 0.7163

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: 3e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
num_epochs: 200

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
1.1435	4.9	500	0.9732	0.6604	0.6283
0.7389	9.8	1000	0.8571	0.6898	0.6780
0.5057	14.71	1500	0.8324	0.6979	0.6929
0.3466	19.61	2000	0.9128	0.6925	0.6945
0.2395	24.51	2500	0.9487	0.7166	0.7192
0.1649	29.41	3000	1.0338	0.7166	0.7172
0.119	34.31	3500	1.1793	0.7112	0.7144
0.0882	39.22	4000	1.2643	0.7166	0.7163

Framework versions

Transformers 4.25.1
Pytorch 1.12.1
Datasets 2.7.1
Tokenizers 0.13.2