metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: atco2_test_set_1h
results: []
atco2_test_set_1h
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: 1.4282
- Precision: 0.6195
- Recall: 0.7071
- F1: 0.6604
- Accuracy: 0.8182
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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 125.0 | 500 | 0.8692 | 0.6396 | 0.7172 | 0.6762 | 0.8307 |
| 0.2158 | 250.0 | 1000 | 1.0074 | 0.5702 | 0.6970 | 0.6273 | 0.8245 |
| 0.2158 | 375.0 | 1500 | 1.3560 | 0.6577 | 0.7374 | 0.6952 | 0.8119 |
| 0.0184 | 500.0 | 2000 | 1.3393 | 0.6182 | 0.6869 | 0.6507 | 0.8056 |
| 0.0184 | 625.0 | 2500 | 1.3528 | 0.6087 | 0.7071 | 0.6542 | 0.8213 |
| 0.0175 | 750.0 | 3000 | 1.4282 | 0.6195 | 0.7071 | 0.6604 | 0.8182 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.0
- Tokenizers 0.13.2