metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- glue
- rte
- max_length_128
- dropout_0.4
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-rte-run_3
results: []
bert-base-uncased-finetuned-rte-run_3
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6286
- Accuracy: 0.6787
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: Use OptimizerNames.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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 78 | 0.6671 | 0.6101 |
| No log | 2.0 | 156 | 0.6286 | 0.6787 |
| No log | 3.0 | 234 | 0.7819 | 0.6282 |
| No log | 4.0 | 312 | 0.9900 | 0.6354 |
| No log | 5.0 | 390 | 1.2262 | 0.6426 |
| No log | 6.0 | 468 | 1.3365 | 0.6462 |
| 0.3699 | 7.0 | 546 | 1.7402 | 0.6426 |
| 0.3699 | 8.0 | 624 | 1.8381 | 0.6426 |
| 0.3699 | 9.0 | 702 | 1.8395 | 0.6462 |
| 0.3699 | 10.0 | 780 | 1.9266 | 0.6354 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1