metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- tweet_eval
metrics:
- f1
base_model: distilbert-base-uncased
model-index:
- name: emotion_trained_final
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: tweet_eval
type: tweet_eval
args: emotion
metrics:
- type: f1
value: 0.7469065445487402
name: F1
emotion_trained_final
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: 0.9349
- F1: 0.7469
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: 1.502523631581398e-05
- train_batch_size: 4
- eval_batch_size: 4
- 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 |
|---|---|---|---|---|
| 0.9013 | 1.0 | 815 | 0.7822 | 0.6470 |
| 0.5008 | 2.0 | 1630 | 0.7142 | 0.7419 |
| 0.3684 | 3.0 | 2445 | 0.8621 | 0.7443 |
| 0.2182 | 4.0 | 3260 | 0.9349 | 0.7469 |
Framework versions
- Transformers 4.12.5
- Pytorch 1.9.1
- Datasets 1.16.1
- Tokenizers 0.10.3