metadata
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: product_classifier_url_name2
results: []
product_classifier_url_name2
This model is a fine-tuned version of bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2686
- Accuracy: 0.9383
- F1: 0.9380
- Precision: 0.9380
- Recall: 0.9383
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.8154 | 1.0 | 960 | 0.3342 | 0.8979 | 0.8979 | 0.8989 | 0.8979 |
| 0.2711 | 2.0 | 1920 | 0.2602 | 0.9279 | 0.9277 | 0.9278 | 0.9279 |
| 0.1624 | 3.0 | 2880 | 0.2528 | 0.9354 | 0.9351 | 0.9356 | 0.9354 |
| 0.109 | 4.0 | 3840 | 0.2686 | 0.9383 | 0.9380 | 0.9380 | 0.9383 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3