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---
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
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