metadata
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: fine-tune-vanilla-bert-base-uncased-ch9
results: []
datasets:
- Francesco-A/github-issues_huggingface-datasets
fine-tune-vanilla-bert-base-uncased-ch9
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1877
- Micro f1: 0.7208
- Macro f1: 0.6293
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Micro f1 | Macro f1 |
|---|---|---|---|---|---|
| 0.4535 | 1.0 | 56 | 0.3607 | 0.0 | 0.0 |
| 0.3388 | 2.0 | 112 | 0.3270 | 0.0 | 0.0 |
| 0.3023 | 3.0 | 168 | 0.2794 | 0.4654 | 0.2139 |
| 0.2515 | 4.0 | 224 | 0.2420 | 0.4750 | 0.1855 |
| 0.2095 | 5.0 | 280 | 0.2263 | 0.5318 | 0.2599 |
| 0.1673 | 6.0 | 336 | 0.2135 | 0.6429 | 0.4327 |
| 0.1424 | 7.0 | 392 | 0.1885 | 0.6631 | 0.4890 |
| 0.1049 | 8.0 | 448 | 0.1801 | 0.7164 | 0.6139 |
| 0.08 | 9.0 | 504 | 0.1802 | 0.7136 | 0.6020 |
| 0.0637 | 10.0 | 560 | 0.1877 | 0.7208 | 0.6293 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.1.0+cu118
- Datasets 1.16.1
- Tokenizers 0.15.0