metadata
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_base_uncased_scotus
results: []
bert_base_uncased_scotus
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: 1.5314
- Accuracy: 0.5514
- F1 Macro: 0.2849
- F1 Micro: 0.5514
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: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
---|---|---|---|---|---|---|
2.0086 | 0.63 | 50 | 2.0065 | 0.3857 | 0.0922 | 0.3857 |
1.5947 | 1.27 | 100 | 1.6981 | 0.475 | 0.1871 | 0.475 |
1.5835 | 1.9 | 150 | 1.5822 | 0.5379 | 0.2780 | 0.5379 |
1.3943 | 2.53 | 200 | 1.5314 | 0.5514 | 0.2849 | 0.5514 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2