End of training
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README.md
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---
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license: apache-2.0
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base_model: google-bert/bert-base-multilingual-cased
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tags:
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This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.
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- Accuracy: 0.
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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-
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- lr_scheduler_type: linear
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- num_epochs:
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### Training results
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| Training Loss | Epoch
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| No log |
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| 0.
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| 0.
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### Framework versions
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- Transformers 4.
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- Pytorch 2.1
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- Datasets
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- Tokenizers 0.
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---
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library_name: transformers
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license: apache-2.0
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base_model: google-bert/bert-base-multilingual-cased
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tags:
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This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2503
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- Precision: 0.7878
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- Recall: 0.8008
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- F1: 0.7942
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- Accuracy: 0.9658
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 16
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 0.9978 | 281 | 0.2317 | 0.6004 | 0.6203 | 0.6102 | 0.9475 |
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| 0.2657 | 1.9973 | 562 | 0.1557 | 0.7484 | 0.7282 | 0.7382 | 0.9629 |
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| 0.2657 | 2.9969 | 843 | 0.1438 | 0.7812 | 0.7925 | 0.7868 | 0.9668 |
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| 0.0848 | 3.9964 | 1124 | 0.1789 | 0.7429 | 0.7614 | 0.7520 | 0.9635 |
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| 0.0848 | 4.9960 | 1405 | 0.2275 | 0.7769 | 0.8091 | 0.7927 | 0.9655 |
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| 0.0378 | 5.9956 | 1686 | 0.1942 | 0.7694 | 0.8237 | 0.7956 | 0.9650 |
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| 0.0378 | 6.9951 | 1967 | 0.2416 | 0.7753 | 0.8091 | 0.7919 | 0.9656 |
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| 0.0192 | 7.9982 | 2249 | 0.2409 | 0.7831 | 0.7863 | 0.7847 | 0.9655 |
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| 0.0084 | 8.9978 | 2530 | 0.2450 | 0.7809 | 0.7988 | 0.7897 | 0.9650 |
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| 0.0084 | 9.9938 | 2810 | 0.2503 | 0.7878 | 0.8008 | 0.7942 | 0.9658 |
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### Framework versions
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- Transformers 4.46.3
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- Pytorch 2.5.1+cu121
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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runs/Dec09_02-31-16_3c066e2cea8b/events.out.tfevents.1733712970.3c066e2cea8b.292.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:2e29ed282f2ebe5460ecec8be9e7e18fa1c473ccbdfe3dd628ae5694c0b9d44a
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size 560
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