metadata
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fine_tuned_cb_bert
results: []
fine_tuned_cb_bert
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: 4.2169
- Accuracy: 0.3636
- F1: 0.2430
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 400
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.7239 | 3.5714 | 50 | 1.2945 | 0.3182 | 0.1536 |
| 0.3879 | 7.1429 | 100 | 1.6236 | 0.4545 | 0.4158 |
| 0.1546 | 10.7143 | 150 | 3.1975 | 0.3636 | 0.2430 |
| 0.0741 | 14.2857 | 200 | 2.9703 | 0.4545 | 0.3895 |
| 0.0323 | 17.8571 | 250 | 3.8104 | 0.3636 | 0.2430 |
| 0.0073 | 21.4286 | 300 | 4.0583 | 0.3636 | 0.2430 |
| 0.0037 | 25.0 | 350 | 4.3166 | 0.3636 | 0.2430 |
| 0.0032 | 28.5714 | 400 | 4.2169 | 0.3636 | 0.2430 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1