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: 0.1408
- Precision: 0.5468
- Recall: 0.4523
- F1: 0.4951
- Accuracy: 0.9518
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 71 | 0.1657 | 0.4603 | 0.2935 | 0.3585 | 0.9383 |
| No log | 2.0 | 142 | 0.1466 | 0.5831 | 0.3838 | 0.4629 | 0.9493 |
| No log | 3.0 | 213 | 0.1408 | 0.5468 | 0.4523 | 0.4951 | 0.9518 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3