bert-large-uncased-kaggle-c
This model is a fine-tuned version of google-bert/bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4620
- Accuracy: 0.8557
- Macro F1: 0.8098
- Micro F1: 0.8557
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: 4
- eval_batch_size: 4
- seed: 42
- 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
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Micro F1 |
|---|---|---|---|---|---|---|
| 0.6051 | 1.0 | 3286 | 0.4620 | 0.8557 | 0.8098 | 0.8557 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for LightFury9/bert-large-uncased-kaggle-c
Base model
google-bert/bert-large-uncased