---
license: cc-by-nc-3.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: finetuning-sentiment-model-bert-multilingual
  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. -->

# finetuning-sentiment-model-bert-multilingual

This model is a fine-tuned version of [QCRI/bert-base-multilingual-cased-pos-english](https://huggingface.co/QCRI/bert-base-multilingual-cased-pos-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9412
- Accuracy: 0.6624
- F1: 0.6624
- Precision: 0.6624
- Recall: 0.6624

## 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: 10

### Training results



### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2