---
license: mit
base_model: nlptown/bert-base-multilingual-uncased-sentiment
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: model_IMDB_bert_base
  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. -->

# model_IMDB_bert_base

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: 0.7390
- Accuracy: 0.9287

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4201        | 1.0   | 6250  | 0.4285          | 0.8902   |
| 0.3454        | 2.0   | 12500 | 0.3388          | 0.9183   |
| 0.2279        | 3.0   | 18750 | 0.3715          | 0.9253   |
| 0.1558        | 4.0   | 25000 | 0.4496          | 0.9244   |
| 0.1047        | 5.0   | 31250 | 0.5458          | 0.9235   |
| 0.0594        | 6.0   | 37500 | 0.6027          | 0.9199   |
| 0.0234        | 7.0   | 43750 | 0.5551          | 0.9254   |
| 0.0281        | 8.0   | 50000 | 0.6457          | 0.9245   |
| 0.0015        | 9.0   | 56250 | 0.7199          | 0.9279   |
| 0.0           | 10.0  | 62500 | 0.7390          | 0.9287   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.17.0
- Tokenizers 0.14.0