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---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: output
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. -->
# output
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9285
- Accuracy: 0.51
## 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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4791 | 1.0 | 94 | 0.8476 | 0.5587 |
| 0.654 | 2.0 | 188 | 0.7250 | 0.564 |
| 0.6278 | 3.0 | 282 | 0.7372 | 0.5393 |
| 0.5884 | 4.0 | 376 | 0.8102 | 0.5503 |
| 0.5493 | 5.0 | 470 | 0.8603 | 0.5183 |
| 0.5265 | 6.0 | 564 | 0.9099 | 0.5213 |
| 0.4908 | 7.0 | 658 | 0.9285 | 0.51 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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