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---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Full-8epoch-BERT-base-multilingual-finetuned-CEFR_ner-60000news
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. -->
# Full-8epoch-BERT-base-multilingual-finetuned-CEFR_ner-60000news
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0772
- Accuracy: 0.3055
- Precision: 0.5539
- Recall: 0.8444
- F1: 0.5463
## 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: 8
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.1609 | 1.0 | 1563 | 0.1237 | 0.3003 | 0.5394 | 0.8062 | 0.5257 |
| 0.1031 | 2.0 | 3126 | 0.0926 | 0.3033 | 0.5628 | 0.8280 | 0.5475 |
| 0.0805 | 3.0 | 4689 | 0.0831 | 0.3043 | 0.5396 | 0.8360 | 0.5317 |
| 0.0687 | 4.0 | 6252 | 0.0789 | 0.3048 | 0.5514 | 0.8404 | 0.5428 |
| 0.0595 | 5.0 | 7815 | 0.0767 | 0.3051 | 0.5386 | 0.8415 | 0.5347 |
| 0.0529 | 6.0 | 9378 | 0.0770 | 0.3053 | 0.5506 | 0.8425 | 0.5444 |
| 0.048 | 7.0 | 10941 | 0.0765 | 0.3055 | 0.5516 | 0.8444 | 0.5451 |
| 0.0453 | 8.0 | 12504 | 0.0772 | 0.3055 | 0.5539 | 0.8444 | 0.5463 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.2.1
- Datasets 2.19.2
- Tokenizers 0.19.1
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