metadata
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: twitter_us_airlines_kaggle_bertweet_base
results: []
twitter_us_airlines_kaggle_bertweet_base
This model is a fine-tuned version of finiteautomata/bertweet-base-sentiment-analysis on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9499
- Accuracy: 0.7920
- F1: 0.7858
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: 2e-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: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 366 | 0.6299 | 0.7493 | 0.7318 |
| 0.7155 | 2.0 | 732 | 0.6029 | 0.7705 | 0.7511 |
| 0.5076 | 3.0 | 1098 | 0.7077 | 0.7633 | 0.7410 |
| 0.5076 | 4.0 | 1464 | 0.6028 | 0.7883 | 0.7748 |
| 0.3971 | 5.0 | 1830 | 0.6514 | 0.7831 | 0.7851 |
| 0.2944 | 6.0 | 2196 | 0.7207 | 0.7900 | 0.7798 |
| 0.2297 | 7.0 | 2562 | 0.7713 | 0.7886 | 0.7788 |
| 0.2297 | 8.0 | 2928 | 0.8283 | 0.7896 | 0.7833 |
| 0.1717 | 9.0 | 3294 | 0.9665 | 0.7828 | 0.7693 |
| 0.1345 | 10.0 | 3660 | 0.9499 | 0.7920 | 0.7858 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.2
- Tokenizers 0.12.1