metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: twitter_trainer
results: []
twitter_trainer
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: 0.7924
- Accuracy: 86.8509
- P: 102.7555
- R: 100.3442
- F1: 101.5355
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | P | R | F1 |
|---|---|---|---|---|---|---|---|
| 3.6245 | 1.0 | 597 | 0.4451 | 84.1709 | 99.8149 | 103.1569 | 101.4584 |
| 1.8323 | 2.0 | 1194 | 0.3794 | 86.0972 | 102.3665 | 100.0625 | 101.2014 |
| 1.233 | 3.0 | 1791 | 0.3715 | 87.5209 | 100.9234 | 102.3408 | 101.6272 |
| 0.9132 | 4.0 | 2388 | 0.5171 | 87.1022 | 102.4483 | 100.4991 | 101.4643 |
| 0.6928 | 5.0 | 2985 | 0.6683 | 86.9347 | 102.6526 | 100.5006 | 101.5652 |
| 0.4037 | 6.0 | 3582 | 0.7477 | 87.3534 | 101.8838 | 101.3746 | 101.6286 |
| 0.3334 | 6.9891 | 4172 | 0.7924 | 86.8509 | 102.7555 | 100.3442 | 101.5355 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0