metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: nli_mbert
results: []
nli_mbert
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: 1.6569
- Accuracy: 0.7419
- Precision: 0.7419
- Recall: 0.7419
- F1 Score: 0.7426
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-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 101
- 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 | Accuracy | Precision | Recall | F1 Score |
|---|---|---|---|---|---|---|---|
| 1.403 | 1.0 | 10330 | 1.3860 | 0.7128 | 0.7128 | 0.7128 | 0.7142 |
| 1.3213 | 2.0 | 20660 | 1.3367 | 0.7365 | 0.7365 | 0.7365 | 0.7371 |
| 1.1611 | 3.0 | 30990 | 1.4699 | 0.7396 | 0.7396 | 0.7396 | 0.7406 |
| 1.0222 | 4.0 | 41320 | 1.6050 | 0.7374 | 0.7374 | 0.7374 | 0.7383 |
| 0.9008 | 5.0 | 51650 | 1.6569 | 0.7419 | 0.7419 | 0.7419 | 0.7426 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3