metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: experiment-model-bertbase
results: []
experiment-model-bertbase
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: 0.8482
- Accuracy: 0.8283
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3481 | 1.0 | 884 | 0.3811 | 0.8241 |
| 0.3027 | 2.0 | 1768 | 0.3705 | 0.8368 |
| 0.2536 | 3.0 | 2652 | 0.4035 | 0.8365 |
| 0.1435 | 4.0 | 3536 | 0.5436 | 0.8224 |
| 0.1124 | 5.0 | 4420 | 0.8482 | 0.8283 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2