metadata
license: mit
base_model: nlptown/bert-base-multilingual-uncased-sentiment
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-multilingual-uncased-sentiment-finetuned-mnli
results: []
bert-base-multilingual-uncased-sentiment-finetuned-mnli
This model is a fine-tuned version of nlptown/bert-base-multilingual-uncased-sentiment on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5330
- Accuracy: 0.7902
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5568 | 1.0 | 1080 | 0.5330 | 0.7902 |
| 0.4713 | 2.0 | 2160 | 0.5633 | 0.7875 |
| 0.3791 | 3.0 | 3240 | 0.6680 | 0.7824 |
| 0.2967 | 4.0 | 4320 | 0.8067 | 0.7624 |
| 0.2121 | 5.0 | 5400 | 0.9723 | 0.7624 |
| 0.1511 | 6.0 | 6480 | 1.1602 | 0.7629 |
| 0.1277 | 7.0 | 7560 | 1.4037 | 0.7736 |
| 0.0931 | 8.0 | 8640 | 1.5388 | 0.7675 |
| 0.0768 | 9.0 | 9720 | 2.0003 | 0.7330 |
| 0.0457 | 10.0 | 10800 | 1.8301 | 0.7756 |
| 0.0383 | 11.0 | 11880 | 1.9697 | 0.7701 |
| 0.0286 | 12.0 | 12960 | 2.0533 | 0.7756 |
| 0.0175 | 13.0 | 14040 | 2.2299 | 0.7594 |
| 0.0101 | 14.0 | 15120 | 2.1549 | 0.7749 |
| 0.0055 | 15.0 | 16200 | 2.2199 | 0.7703 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1