metadata
license: apache-2.0
base_model: distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: NLP-HIBA2_DisTEMIST_fine_tuned_biobert-pretrained-model
results: []
NLP-HIBA2_DisTEMIST_fine_tuned_biobert-pretrained-model
This model is a fine-tuned version of distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1602
- Precision: 0.5278
- Recall: 0.4527
- F1: 0.4874
- Accuracy: 0.9479
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 71 | 0.1798 | 0.3590 | 0.2669 | 0.3062 | 0.9316 |
| No log | 2.0 | 142 | 0.1570 | 0.4772 | 0.3407 | 0.3976 | 0.9433 |
| No log | 3.0 | 213 | 0.1506 | 0.4967 | 0.4245 | 0.4578 | 0.9456 |
| No log | 4.0 | 284 | 0.1601 | 0.5402 | 0.4297 | 0.4787 | 0.9485 |
| No log | 5.0 | 355 | 0.1602 | 0.5278 | 0.4527 | 0.4874 | 0.9479 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1