metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: TTC4900Model
results: []
TTC4900Model
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: 0.0667
- Accuracy: 0.9859
- F1: 0.9418
- Precision: 0.9562
- Recall: 0.9309
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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 1.5192 | 0.3289 | 50 | 0.9342 | 0.7575 | 0.1077 | 0.0947 | 0.125 |
| 0.6007 | 0.6579 | 100 | 0.4256 | 0.8767 | 0.3189 | 0.2983 | 0.3445 |
| 0.2704 | 0.9868 | 150 | 0.2471 | 0.9561 | 0.6877 | 0.6916 | 0.6917 |
| 0.1382 | 1.3158 | 200 | 0.1346 | 0.9727 | 0.8789 | 0.9054 | 0.8698 |
| 0.1132 | 1.6447 | 250 | 0.0824 | 0.9876 | 0.9350 | 0.9701 | 0.9103 |
| 0.0981 | 1.9737 | 300 | 0.0431 | 0.9942 | 0.9749 | 0.9892 | 0.9635 |
| 0.0369 | 2.3026 | 350 | 0.0466 | 0.9892 | 0.9376 | 0.9576 | 0.9275 |
| 0.0373 | 2.6316 | 400 | 0.0413 | 0.9909 | 0.9602 | 0.9580 | 0.9630 |
| 0.0235 | 2.9605 | 450 | 0.0407 | 0.9909 | 0.9613 | 0.9600 | 0.9630 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1