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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - tweet_eval
metrics:
  - accuracy
  - f1
model-index:
  - name: tiny-mlm-imdb-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: 0.6925133689839572
          - name: F1
            type: f1
            value: 0.7003562110650444

tiny-mlm-imdb-target-tweet

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

  • Loss: 1.5550
  • Accuracy: 0.6925
  • F1: 0.7004

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
1.159 4.9 500 0.9977 0.6364 0.6013
0.7514 9.8 1000 0.8549 0.7112 0.7026
0.5011 14.71 1500 0.8516 0.7032 0.6962
0.34 19.61 2000 0.9019 0.7059 0.7030
0.2258 24.51 2500 0.9722 0.7166 0.7164
0.1607 29.41 3000 1.0724 0.6979 0.6999
0.1127 34.31 3500 1.1435 0.7193 0.7169
0.0791 39.22 4000 1.2807 0.7059 0.7069
0.0568 44.12 4500 1.3849 0.7139 0.7159
0.0478 49.02 5000 1.5550 0.6925 0.7004

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.12.1
  • Datasets 2.7.1
  • Tokenizers 0.13.2