metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: text_classification
results: []
text_classification
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: 0.3130
- Accuracy: 0.9296
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: 4
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0246 | 0.1 | 625 | 0.5761 | 0.8912 |
| 1.1268 | 0.2 | 1250 | 0.5357 | 0.8916 |
| 1.5699 | 0.3 | 1875 | 0.5982 | 0.8884 |
| 1.0828 | 0.4 | 2500 | 0.3852 | 0.9128 |
| 0.003 | 0.5 | 3125 | 0.3994 | 0.9236 |
| 1.065 | 0.6 | 3750 | 0.3597 | 0.9248 |
| 1.1396 | 0.7 | 4375 | 0.3357 | 0.9272 |
| 0.0024 | 0.8 | 5000 | 0.3534 | 0.9276 |
| 0.0132 | 0.9 | 5625 | 0.3212 | 0.9304 |
| 0.0065 | 1.0 | 6250 | 0.3130 | 0.9296 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2