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license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: BiBert-Classification
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. -->
# BiBert-Classification
This model is a fine-tuned version of [nlptown/bert-base-multilingual-uncased-sentiment](https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0853
- Accuracy: 0.7433
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0981 | 1.0 | 9718 | 1.1034 | 0.7328 |
| 1.0394 | 2.0 | 19436 | 1.0853 | 0.7433 |
| 0.9649 | 3.0 | 29154 | 1.1041 | 0.7362 |
| 0.8884 | 4.0 | 38872 | 1.1618 | 0.7315 |
| 0.8005 | 5.0 | 48590 | 1.2340 | 0.7251 |
### Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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