metadata
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 16_combo_webscrap_1709_v2_reduce_others
results: []
16_combo_webscrap_1709_v2_reduce_others
This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1501
- Accuracy: 0.9636
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 363 | 1.0481 | 0.7263 |
| 1.5287 | 2.0 | 726 | 0.5613 | 0.8655 |
| 0.6856 | 3.0 | 1089 | 0.3666 | 0.9121 |
| 0.6856 | 4.0 | 1452 | 0.2880 | 0.9284 |
| 0.4313 | 5.0 | 1815 | 0.2187 | 0.9464 |
| 0.3097 | 6.0 | 2178 | 0.1992 | 0.9505 |
| 0.2454 | 7.0 | 2541 | 0.1627 | 0.9598 |
| 0.2454 | 8.0 | 2904 | 0.1501 | 0.9636 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3