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---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bert_product_classifier_final
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_product_classifier_final
This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2344
- Accuracy: 0.9470
- F1: 0.9466
- Precision: 0.9467
- Recall: 0.9470
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.85 | 1.0 | 960 | 0.2943 | 0.9090 | 0.9074 | 0.9091 | 0.9090 |
| 0.2538 | 2.0 | 1920 | 0.2250 | 0.9332 | 0.9331 | 0.9331 | 0.9332 |
| 0.1468 | 3.0 | 2880 | 0.2372 | 0.9384 | 0.9388 | 0.9396 | 0.9384 |
| 0.0937 | 4.0 | 3840 | 0.2344 | 0.9470 | 0.9466 | 0.9467 | 0.9470 |
### Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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