metadata
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: NLP-CIC-WFU_DisTEMIST_fine_tuned_bert-base-multilingual-cased
results: []
NLP-CIC-WFU_DisTEMIST_fine_tuned_bert-base-multilingual-cased
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: 0.1620
- Precision: 0.6121
- Recall: 0.5161
- F1: 0.5600
- Accuracy: 0.9541
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 71 | 0.1704 | 0.4558 | 0.3635 | 0.4045 | 0.9353 |
| No log | 2.0 | 142 | 0.1572 | 0.5925 | 0.3518 | 0.4415 | 0.9433 |
| No log | 3.0 | 213 | 0.1386 | 0.5932 | 0.4774 | 0.5290 | 0.9531 |
| No log | 4.0 | 284 | 0.1427 | 0.5945 | 0.5175 | 0.5534 | 0.9533 |
| No log | 5.0 | 355 | 0.1653 | 0.6354 | 0.4788 | 0.5461 | 0.9540 |
| No log | 6.0 | 426 | 0.1620 | 0.6121 | 0.5161 | 0.5600 | 0.9541 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1