metadata
base_model: google-bert/bert-base-multilingual-cased
library_name: transformers
license: apache-2.0
metrics:
- accuracy
- f1
- precision
- recall
tags:
- generated_from_trainer
model-index:
- name: bert-base-multilingual-cased-intent-booking
results: []
bert-base-multilingual-cased-intent-booking
This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3045
- Accuracy: 0.9189
- F1: 0.9155
- Precision: 0.9322
- Recall: 0.9189
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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 64
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 2.246 | 1.0 | 65 | 1.7430 | 0.4730 | 0.3680 | 0.3529 | 0.4730 |
| 0.972 | 2.0 | 130 | 0.3620 | 0.9369 | 0.9371 | 0.9417 | 0.9369 |
| 0.3069 | 3.0 | 195 | 0.2379 | 0.9414 | 0.9412 | 0.9490 | 0.9414 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1