metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - tweet_eval
metrics:
  - f1
base_model: distilbert-base-uncased
model-index:
  - name: demo_hate_1234567
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: tweet_eval
          type: tweet_eval
          args: hate
        metrics:
          - type: f1
            value: 0.7772939485986298
            name: F1

demo_hate_1234567

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: 0.8697
F1: 0.7773

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: 7.320702985778492e-05
train_batch_size: 32
eval_batch_size: 32
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	282	0.4850	0.7645
0.3877	2.0	564	0.5160	0.7856
0.3877	3.0	846	0.6927	0.7802
0.1343	4.0	1128	0.8697	0.7773

Framework versions

Transformers 4.12.5
Pytorch 1.9.1
Datasets 1.16.1
Tokenizers 0.10.3