---
library_name: transformers
license: mit
base_model: nlptown/bert-base-multilingual-uncased-sentiment
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-multilingual-uncased-sentiment_v3
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert-base-multilingual-uncased-sentiment_v3

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: 0.4987
- Accuracy: 0.9286
- Precision Macro: 0.8226
- Recall Macro: 0.7931
- F1 Macro: 0.8061
- F1 Weighted: 0.9269

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1 Macro | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:-----------:|
| 0.3933        | 1.0   | 90   | 0.2349          | 0.9292   | 0.8484          | 0.7197       | 0.7474   | 0.9202      |
| 0.2051        | 2.0   | 180  | 0.2166          | 0.9236   | 0.8134          | 0.7619       | 0.7811   | 0.9199      |
| 0.1494        | 3.0   | 270  | 0.2369          | 0.9362   | 0.8619          | 0.7775       | 0.8072   | 0.9321      |
| 0.1233        | 4.0   | 360  | 0.2290          | 0.9343   | 0.8660          | 0.7894       | 0.8176   | 0.9309      |
| 0.0838        | 5.0   | 450  | 0.2490          | 0.9375   | 0.8610          | 0.8200       | 0.8378   | 0.9358      |
| 0.0799        | 6.0   | 540  | 0.2579          | 0.9343   | 0.8528          | 0.7977       | 0.8197   | 0.9317      |
| 0.0481        | 7.0   | 630  | 0.3494          | 0.9223   | 0.7926          | 0.8252       | 0.8064   | 0.9247      |
| 0.0406        | 8.0   | 720  | 0.3154          | 0.9368   | 0.8591          | 0.7986       | 0.8227   | 0.9341      |
| 0.032         | 9.0   | 810  | 0.3219          | 0.9305   | 0.8238          | 0.8153       | 0.8194   | 0.9301      |
| 0.0333        | 10.0  | 900  | 0.3787          | 0.9286   | 0.8387          | 0.8048       | 0.8198   | 0.9270      |
| 0.0278        | 11.0  | 990  | 0.3914          | 0.9311   | 0.8432          | 0.7948       | 0.8148   | 0.9288      |
| 0.0165        | 12.0  | 1080 | 0.4155          | 0.9318   | 0.8627          | 0.7830       | 0.8120   | 0.9282      |
| 0.0126        | 13.0  | 1170 | 0.4029          | 0.9368   | 0.8550          | 0.8161       | 0.8328   | 0.9352      |
| 0.0133        | 14.0  | 1260 | 0.4398          | 0.9324   | 0.8460          | 0.7915       | 0.8134   | 0.9297      |
| 0.01          | 15.0  | 1350 | 0.4571          | 0.9318   | 0.8347          | 0.7913       | 0.8094   | 0.9294      |
| 0.008         | 16.0  | 1440 | 0.4685          | 0.9299   | 0.8303          | 0.7899       | 0.8070   | 0.9276      |
| 0.0058        | 17.0  | 1530 | 0.4846          | 0.9318   | 0.8403          | 0.7954       | 0.8142   | 0.9295      |
| 0.0022        | 18.0  | 1620 | 0.4905          | 0.9280   | 0.8249          | 0.7928       | 0.8068   | 0.9262      |
| 0.0038        | 19.0  | 1710 | 0.5043          | 0.9299   | 0.8272          | 0.7897       | 0.8057   | 0.9277      |
| 0.0015        | 20.0  | 1800 | 0.4987          | 0.9286   | 0.8226          | 0.7931       | 0.8061   | 0.9269      |


### Framework versions

- Transformers 4.55.0
- Pytorch 2.7.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4