metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- tweet_eval
metrics:
- f1
model-index:
- name: presentation_irony_31415
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: tweet_eval
type: tweet_eval
args: irony
metrics:
- name: F1
type: f1
value: 0.6753923142373446
presentation_irony_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: 0.9694
- F1: 0.6754
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: 5.1637764704815665e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|---|
| 0.6601 | 1.0 | 90 | 0.6298 | 0.6230 |
| 0.4887 | 2.0 | 180 | 0.6039 | 0.6816 |
| 0.2543 | 3.0 | 270 | 0.7362 | 0.6803 |
| 0.1472 | 4.0 | 360 | 0.9694 | 0.6754 |
Framework versions
- Transformers 4.12.5
- Pytorch 1.9.1
- Datasets 1.16.1
- Tokenizers 0.10.3