metadata
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hf-bert-finetuning
results: []
hf-bert-finetuning
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.2672
- Accuracy: 0.805
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.392 | 4.0 | 500 | 1.1767 | 0.805 |
| 0.0421 | 8.0 | 1000 | 1.3555 | 0.814 |
| 0.0266 | 12.0 | 1500 | 1.7734 | 0.806 |
| 0.0066 | 16.0 | 2000 | 1.6149 | 0.818 |
| 0.0264 | 20.0 | 2500 | 1.4583 | 0.823 |
| 0.0284 | 24.0 | 3000 | 1.8117 | 0.794 |
| 0.0019 | 28.0 | 3500 | 1.8569 | 0.804 |
| 0.0336 | 32.0 | 4000 | 1.8200 | 0.801 |
| 0.0221 | 36.0 | 4500 | 1.8082 | 0.806 |
| 0.0195 | 40.0 | 5000 | 1.8102 | 0.81 |
| 0.007 | 44.0 | 5500 | 1.9712 | 0.82 |
| 0.0028 | 48.0 | 6000 | 1.8803 | 0.818 |
| 0.0017 | 52.0 | 6500 | 1.9739 | 0.82 |
| 0.0 | 56.0 | 7000 | 2.0171 | 0.821 |
| 0.019 | 60.0 | 7500 | 1.9017 | 0.805 |
| 0.0 | 64.0 | 8000 | 2.0914 | 0.801 |
| 0.0 | 68.0 | 8500 | 2.1453 | 0.799 |
| 0.0061 | 72.0 | 9000 | 2.2067 | 0.786 |
| 0.0009 | 76.0 | 9500 | 2.1612 | 0.799 |
| 0.0026 | 80.0 | 10000 | 2.1481 | 0.807 |
| 0.0 | 84.0 | 10500 | 2.1813 | 0.807 |
| 0.0 | 88.0 | 11000 | 2.2069 | 0.807 |
| 0.0 | 92.0 | 11500 | 2.2285 | 0.807 |
| 0.0 | 96.0 | 12000 | 2.2422 | 0.807 |
| 0.0004 | 100.0 | 12500 | 2.2672 | 0.805 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1