---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-multilingual-uncased-sentiment-finetuned-mnli

This model is a fine-tuned version of [nlptown/bert-base-multilingual-uncased-sentiment](https://huggingface.co/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