metadata
license: apache-2.0
base_model: distilbert/distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: NEW_trained_english
results: []
NEW_trained_english
This model is a fine-tuned version of distilbert/distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1146
- Precision: 0.7363
- Recall: 0.7212
- F1: 0.7287
- Accuracy: 0.9767
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1114 | 1.0 | 784 | 0.0881 | 0.7161 | 0.7397 | 0.7277 | 0.9756 |
| 0.0308 | 2.0 | 1568 | 0.1023 | 0.7348 | 0.6738 | 0.7030 | 0.9749 |
| 0.0155 | 3.0 | 2352 | 0.1055 | 0.7588 | 0.7109 | 0.7340 | 0.9775 |
| 0.0062 | 4.0 | 3136 | 0.1146 | 0.7363 | 0.7212 | 0.7287 | 0.9767 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2