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: 0.1367
- Precision: 0.5765
- Recall: 0.4800
- F1: 0.5238
- Accuracy: 0.9535
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 | 0.1588 | 0.4782 | 0.3308 | 0.3911 | 0.9408 |
| No log | 2.0 | 142 | 0.1397 | 0.5760 | 0.4213 | 0.4866 | 0.9517 |
| No log | 3.0 | 213 | 0.1367 | 0.5765 | 0.4800 | 0.5238 | 0.9535 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3