metadata
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: assignment2_attempt12
results: []
assignment2_attempt12
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4465
- Precision: 0.2230
- Recall: 0.2268
- F1: 0.2249
- Accuracy: 0.9262
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
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 347 | 0.2699 | 0.1554 | 0.1581 | 0.1567 | 0.9238 |
| 0.3071 | 2.0 | 694 | 0.3111 | 0.1843 | 0.1375 | 0.1575 | 0.9302 |
| 0.1235 | 3.0 | 1041 | 0.3048 | 0.2164 | 0.2543 | 0.2338 | 0.9280 |
| 0.1235 | 4.0 | 1388 | 0.3606 | 0.1920 | 0.2302 | 0.2094 | 0.9208 |
| 0.0592 | 5.0 | 1735 | 0.4584 | 0.2112 | 0.1684 | 0.1874 | 0.9280 |
| 0.0304 | 6.0 | 2082 | 0.4465 | 0.2230 | 0.2268 | 0.2249 | 0.9262 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1