| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google-bert/bert-base-multilingual-cased |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: multilingual_bert_AGRO |
| 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. --> |
|
|
| # multilingual_bert_AGRO |
|
|
| This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 4.9701 |
| - Exact Match: 24.8571 |
| - F1 Score: 56.8185 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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|
| The following hyperparameters were used during training: |
| - learning_rate: 1e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 3407 |
| - gradient_accumulation_steps: 16 |
| - total_train_batch_size: 64 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.1 |
| - training_steps: 50 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 Score | |
| |:-------------:|:------:|:----:|:---------------:|:-----------:|:--------:| |
| | 6.2135 | 0.0053 | 1 | 6.2224 | 0.0 | 9.8241 | |
| | 6.2165 | 0.0107 | 2 | 6.1874 | 0.0 | 9.8716 | |
| | 6.1776 | 0.0160 | 3 | 6.1182 | 0.0 | 10.1769 | |
| | 6.1126 | 0.0214 | 4 | 6.0144 | 0.0 | 11.2194 | |
| | 6.0166 | 0.0267 | 5 | 5.8717 | 0.0752 | 12.2552 | |
| | 5.8816 | 0.0321 | 6 | 5.6741 | 2.2556 | 18.5657 | |
| | 5.7374 | 0.0374 | 7 | 5.4450 | 12.1805 | 37.6517 | |
| | 5.5652 | 0.0428 | 8 | 5.1969 | 23.8346 | 53.3283 | |
| | 5.2962 | 0.0481 | 9 | 4.9758 | 26.5414 | 56.9819 | |
| | 5.0538 | 0.0535 | 10 | 4.8192 | 22.1805 | 56.7266 | |
| | 5.0246 | 0.0588 | 11 | 4.6919 | 18.2707 | 56.2903 | |
| | 4.8358 | 0.0641 | 12 | 4.5354 | 18.2707 | 56.7852 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.46.3 |
| - Pytorch 2.4.0 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
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|
