bert-large-cased-rocstories
This model is a fine-tuned version of bert-large-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2812
- Accuracy: 0.9417
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 150 | 0.2881 | 0.8778 |
| No log | 2.0 | 300 | 0.2023 | 0.9248 |
| No log | 3.0 | 450 | 0.2607 | 0.9417 |
| 0.2327 | 4.0 | 600 | 0.2812 | 0.9417 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for KeiHeityuu/bert-large-cased-rocstories
Base model
google-bert/bert-large-cased