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End of training

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README.md CHANGED
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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:
@@ -20,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.1455
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- - Precision: 0.7348
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- - Recall: 0.7531
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- - F1: 0.7439
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- - Accuracy: 0.9602
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  ## Model description
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@@ -44,26 +45,34 @@ More information needed
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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: 16
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- - eval_batch_size: 16
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  - seed: 42
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- - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 
 
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  - lr_scheduler_type: linear
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- - num_epochs: 100
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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 | 1.0 | 282 | 0.1751 | 0.6608 | 0.6992 | 0.6794 | 0.9537 |
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- | 0.2367 | 2.0 | 564 | 0.1455 | 0.7348 | 0.7531 | 0.7439 | 0.9602 |
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- | 0.2367 | 3.0 | 846 | 0.1494 | 0.7395 | 0.7656 | 0.7523 | 0.9640 |
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- | 0.0717 | 4.0 | 1128 | 0.1696 | 0.7341 | 0.7676 | 0.7505 | 0.9603 |
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.41.1
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- - Pytorch 2.1.2
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- - Datasets 2.19.1
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- - Tokenizers 0.19.1
 
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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
runs/Dec09_02-31-16_3c066e2cea8b/events.out.tfevents.1733712970.3c066e2cea8b.292.1 ADDED
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+ oid sha256:2e29ed282f2ebe5460ecec8be9e7e18fa1c473ccbdfe3dd628ae5694c0b9d44a
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+ size 560