metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-cased-twitter_sentiment
results: []
bert-base-cased-twitter_sentiment
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6907
- Accuracy: 0.7132
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: 1e-06
- train_batch_size: 8
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|
| 0.8901 | 1.0 | 1387 | 0.8592 | 0.6249 |
| 0.8085 | 2.0 | 2774 | 0.7600 | 0.6822 |
| 0.7336 | 3.0 | 4161 | 0.7170 | 0.6915 |
| 0.6938 | 4.0 | 5548 | 0.7018 | 0.7016 |
| 0.6738 | 5.0 | 6935 | 0.6926 | 0.7067 |
| 0.6496 | 6.0 | 8322 | 0.6910 | 0.7088 |
| 0.6599 | 7.0 | 9709 | 0.6902 | 0.7088 |
| 0.631 | 8.0 | 11096 | 0.6910 | 0.7095 |
| 0.6327 | 9.0 | 12483 | 0.6925 | 0.7146 |
| 0.6305 | 10.0 | 13870 | 0.6907 | 0.7132 |
Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3