metadata
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- recall
- f1
- accuracy
model-index:
- name: bert-base-multilingual-cased-finetune-claim
results: []
bert-base-multilingual-cased-finetune-claim
This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4472
- Precison: 0.7782
- Recall: 0.7803
- F1: 0.7792
- Accuracy: 0.7891
- Jaccard: 0.5779
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precison | Recall | F1 | Accuracy | Jaccard |
|---|---|---|---|---|---|---|---|---|
| 0.411 | 1.0 | 1513 | 0.3212 | 0.8524 | 0.8559 | 0.8540 | 0.8578 | 0.7817 |
| 0.3154 | 2.0 | 3026 | 0.3158 | 0.8639 | 0.8630 | 0.8634 | 0.8678 | 0.7984 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1