|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_keras_callback |
|
model-index: |
|
- name: xmelus/mbert |
|
results: [] |
|
--- |
|
|
|
This is a model card copied from original Tensorflow model version: https://huggingface.co/fimu-docproc-research/mbert-finetuned |
|
|
|
# xmelus/mbert |
|
|
|
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Train Loss: 1.5424 |
|
- Train Accuracy: 0.1446 |
|
- Validation Loss: 1.5269 |
|
- Validation Accuracy: 0.1461 |
|
- Finished epochs: 24 |
|
|
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -596, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01} |
|
- training_precision: mixed_float16 |
|
|
|
### Training results |
|
|
|
Epoch 1/50 |
|
|
|
loss: 2.9925 - accuracy: 0.1059 - val_loss: 1.9812 - val_accuracy: 0.1331 |
|
|
|
Epoch 2/50 |
|
|
|
loss: 1.9979 - accuracy: 0.1307 - val_loss: 1.6063 - val_accuracy: 0.1429 |
|
|
|
Epoch 3/50 |
|
|
|
loss: 1.5798 - accuracy: 0.1434 - val_loss: 1.5332 - val_accuracy: 0.1461 |
|
|
|
Epoch 4/50 |
|
|
|
loss: 1.5325 - accuracy: 0.1451 - val_loss: 1.5285 - val_accuracy: 0.1458 |
|
|
|
Epoch 5/50 |
|
|
|
loss: 1.5415 - accuracy: 0.1448 - val_loss: 1.5449 - val_accuracy: 0.1457 |
|
|
|
Epoch 6/50 |
|
|
|
loss: 1.5395 - accuracy: 0.1448 - val_loss: 1.5448 - val_accuracy: 0.1456 |
|
|
|
Epoch 7/50 |
|
|
|
loss: 1.5463 - accuracy: 0.1446 - val_loss: 1.5421 - val_accuracy: 0.1454 |
|
|
|
Epoch 8/50 |
|
|
|
loss: 1.5352 - accuracy: 0.1451 - val_loss: 1.5536 - val_accuracy: 0.1453 |
|
|
|
Epoch 9/50 |
|
|
|
oss: 1.5230 - accuracy: 0.1451 - val_loss: 1.5097 - val_accuracy: 0.1466 |
|
|
|
Epoch 10/50 |
|
|
|
loss: 1.5318 - accuracy: 0.1449 - val_loss: 1.5303 - val_accuracy: 0.1460 |
|
|
|
Epoch 11/50 |
|
|
|
loss: 1.5364 - accuracy: 0.1448 - val_loss: 1.5280 - val_accuracy: 0.1462 |
|
|
|
Epoch 12/50 |
|
|
|
loss: 1.5411 - accuracy: 0.1444 - val_loss: 1.5493 - val_accuracy: 0.1455 |
|
|
|
Epoch 13/50 |
|
|
|
loss: 1.5378 - accuracy: 0.1446 - val_loss: 1.5473 - val_accuracy: 0.1456 |
|
|
|
Epoch 14/50 |
|
|
|
loss: 1.5357 - accuracy: 0.1449 - val_loss: 1.5310 - val_accuracy: 0.1457 |
|
|
|
Epoch 15/50 |
|
|
|
loss: 1.5424 - accuracy: 0.1446 - val_loss: 1.5269 - val_accuracy: 0.1461 |
|
|
|
Epoch 16/50 |
|
|
|
loss: 1.5314 - accuracy: 0.1450 - val_loss: 1.5392 - val_accuracy: 0.1456 |
|
|
|
Epoch 17/50 |
|
|
|
loss: 1.5309 - accuracy: 0.1451 - val_loss: 1.5567 - val_accuracy: 0.1454 |
|
|
|
Epoch 18/50 |
|
|
|
loss: 1.5279 - accuracy: 0.1450 - val_loss: 1.5561 - val_accuracy: 0.1452 |
|
|
|
Epoch 19/50 |
|
|
|
loss: 1.5311 - accuracy: 0.1450 - val_loss: 1.5400 - val_accuracy: 0.1460 |
|
|
|
Epoch 20/50 |
|
|
|
loss: 1.5332 - accuracy: 0.1449 - val_loss: 1.5347 - val_accuracy: 0.1460 |
|
|
|
Epoch 21/50 |
|
|
|
loss: 1.5319 - accuracy: 0.1452 - val_loss: 1.5410 - val_accuracy: 0.1458 |
|
|
|
Epoch 22/50 |
|
|
|
loss: 1.5327 - accuracy: 0.1449 - val_loss: 1.5352 - val_accuracy: 0.1460 |
|
|
|
Epoch 23/50 |
|
|
|
loss: 1.5278 - accuracy: 0.1451 - val_loss: 1.5289 - val_accuracy: 0.1458 |
|
|
|
Epoch 24/50 |
|
|
|
loss: 1.5234 - accuracy: 0.1451 - val_loss: 1.5568 - val_accuracy: 0.1449 |
|
|
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.22.1 |
|
- Torch 1.13.1 |
|
- Datasets 2.5.1 |
|
- Tokenizers 0.12.1 |
|
|
