metadata
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Full-2epoch-BERT-base-multilingual-finetuned-CEFR_ner-60000news
results: []
Full-2epoch-BERT-base-multilingual-finetuned-CEFR_ner-60000news
This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1113
- Accuracy: 0.3015
- Precision: 0.5856
- Recall: 0.8155
- F1: 0.5650
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.1704 | 1.0 | 1563 | 0.1348 | 0.2991 | 0.5538 | 0.7961 | 0.5345 |
0.1196 | 2.0 | 3126 | 0.1113 | 0.3015 | 0.5856 | 0.8155 | 0.5650 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.2.1
- Datasets 2.19.2
- Tokenizers 0.19.1