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: 0.7043
- F1: 0.8593
- Recall: 0.9046
- Accuracy: 0.9046
- Precision: 0.8183
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: 0.0001
- 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 |
|---|---|---|---|---|---|---|---|
| 0.2575 | 1.0 | 1195 | 0.6712 | 0.8593 | 0.9046 | 0.9046 | 0.8183 |
| 0.2478 | 2.0 | 2390 | 0.6663 | 0.8593 | 0.9046 | 0.9046 | 0.8183 |
| 0.254 | 3.0 | 3585 | 0.6704 | 0.8593 | 0.9046 | 0.9046 | 0.8183 |
| 0.2905 | 4.0 | 4780 | 0.6748 | 0.8593 | 0.9046 | 0.9046 | 0.8183 |
| 0.2531 | 5.0 | 5975 | 0.7043 | 0.8593 | 0.9046 | 0.9046 | 0.8183 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3