metadata
license: apache-2.0
base_model: google-bert/bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: nlp_1
results: []
nlp_1
This model is a fine-tuned version of google-bert/bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4215
- Accuracy: 0.9037
- Precision: 0.8944
- Recall: 0.9025
- F1: 0.8968
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.3252 | 1.0 | 48 | 0.4194 | 0.8670 | 0.8671 | 0.8619 | 0.8617 |
| 0.1803 | 2.0 | 96 | 0.3779 | 0.8853 | 0.8807 | 0.8788 | 0.8773 |
| 0.1713 | 3.0 | 144 | 0.4097 | 0.8945 | 0.8864 | 0.8924 | 0.8857 |
| 0.1359 | 4.0 | 192 | 0.4012 | 0.8945 | 0.8919 | 0.8841 | 0.8873 |
| 0.1201 | 5.0 | 240 | 0.3770 | 0.8899 | 0.8809 | 0.8876 | 0.8818 |
| 0.0735 | 6.0 | 288 | 0.4204 | 0.8991 | 0.8934 | 0.8975 | 0.8921 |
| 0.0807 | 7.0 | 336 | 0.4092 | 0.9083 | 0.9059 | 0.9020 | 0.9024 |
| 0.1066 | 8.0 | 384 | 0.4181 | 0.8991 | 0.8894 | 0.8928 | 0.8903 |
| 0.0615 | 9.0 | 432 | 0.4212 | 0.9083 | 0.8988 | 0.9066 | 0.9014 |
| 0.071 | 10.0 | 480 | 0.4215 | 0.9037 | 0.8944 | 0.9025 | 0.8968 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1