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---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert_seed36_1311
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. -->
# multibert_seed36_1311
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: 0.4419
- Precisions: 0.8943
- Recall: 0.8153
- F-measure: 0.8493
- Accuracy: 0.9385
## 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: 7.5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 36
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 14
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4359 | 1.0 | 236 | 0.3021 | 0.8474 | 0.6948 | 0.7163 | 0.9077 |
| 0.2293 | 2.0 | 472 | 0.2484 | 0.8612 | 0.7522 | 0.7842 | 0.9258 |
| 0.1373 | 3.0 | 708 | 0.3033 | 0.7969 | 0.7892 | 0.7776 | 0.9250 |
| 0.0881 | 4.0 | 944 | 0.3218 | 0.8153 | 0.8103 | 0.8094 | 0.9299 |
| 0.0612 | 5.0 | 1180 | 0.3208 | 0.8357 | 0.8151 | 0.8225 | 0.9315 |
| 0.0378 | 6.0 | 1416 | 0.3553 | 0.8919 | 0.8173 | 0.8493 | 0.9405 |
| 0.0283 | 7.0 | 1652 | 0.4053 | 0.8575 | 0.8070 | 0.8270 | 0.9364 |
| 0.0229 | 8.0 | 1888 | 0.3789 | 0.8639 | 0.8236 | 0.8398 | 0.9354 |
| 0.0149 | 9.0 | 2124 | 0.4101 | 0.8856 | 0.8070 | 0.8387 | 0.9376 |
| 0.0073 | 10.0 | 2360 | 0.4419 | 0.8943 | 0.8153 | 0.8493 | 0.9385 |
| 0.0036 | 11.0 | 2596 | 0.4621 | 0.8882 | 0.8045 | 0.8392 | 0.9371 |
| 0.0045 | 12.0 | 2832 | 0.4494 | 0.8913 | 0.8093 | 0.8440 | 0.9383 |
| 0.0034 | 13.0 | 3068 | 0.4420 | 0.8795 | 0.8152 | 0.8422 | 0.9395 |
| 0.0014 | 14.0 | 3304 | 0.4494 | 0.8838 | 0.8100 | 0.8404 | 0.9390 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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