metadata
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- f1
- recall
- accuracy
- precision
model-index:
- name: bert-base-fine-tuned-text-classificarion-ds
results: []
bert-base-fine-tuned-text-classificarion-ds
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: 0.9226
- F1: 0.7658
- Recall: 0.7781
- Accuracy: 0.7781
- Precision: 0.7732
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Accuracy | Precision |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 442 | 1.6778 | 0.5689 | 0.6220 | 0.6220 | 0.5666 |
| 2.5427 | 2.0 | 884 | 1.2190 | 0.6737 | 0.7091 | 0.7091 | 0.6681 |
| 1.2661 | 3.0 | 1326 | 1.0742 | 0.7099 | 0.7440 | 0.7440 | 0.7132 |
| 0.8666 | 4.0 | 1768 | 1.0213 | 0.7374 | 0.7526 | 0.7526 | 0.7447 |
| 0.6456 | 5.0 | 2210 | 0.9226 | 0.7658 | 0.7781 | 0.7781 | 0.7732 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3