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result-colab

Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Inference Endpoints
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End of training

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  1. README.md +14 -16
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ 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-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3660
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- - Accuracy: 0.8991
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- - Precision: 0.8990
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- - Recall: 0.8942
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- - F1: 0.8959
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  ## Model description
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@@ -49,22 +49,20 @@ The following hyperparameters were used during training:
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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: cosine
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- - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 0.3839 | 1.0 | 24 | 0.4077 | 0.8716 | 0.8635 | 0.8717 | 0.8639 |
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- | 0.3268 | 2.0 | 48 | 0.4052 | 0.8578 | 0.8510 | 0.8489 | 0.8467 |
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- | 0.2524 | 3.0 | 72 | 0.4014 | 0.8899 | 0.8938 | 0.8795 | 0.8843 |
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- | 0.2171 | 4.0 | 96 | 0.3582 | 0.8899 | 0.8860 | 0.8849 | 0.8846 |
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- | 0.1712 | 5.0 | 120 | 0.3983 | 0.8899 | 0.8885 | 0.8804 | 0.8826 |
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- | 0.1627 | 6.0 | 144 | 0.3789 | 0.8991 | 0.8984 | 0.8998 | 0.8983 |
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- | 0.1462 | 7.0 | 168 | 0.3884 | 0.8991 | 0.9004 | 0.8922 | 0.8955 |
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- | 0.1499 | 8.0 | 192 | 0.3727 | 0.9083 | 0.9069 | 0.9080 | 0.9070 |
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- | 0.1557 | 9.0 | 216 | 0.3669 | 0.8991 | 0.8990 | 0.8942 | 0.8959 |
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- | 0.1462 | 10.0 | 240 | 0.3660 | 0.8991 | 0.8990 | 0.8942 | 0.8959 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4210
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+ - Accuracy: 0.9083
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+ - Precision: 0.9076
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+ - Recall: 0.9099
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+ - F1: 0.9085
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  ## Model description
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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: cosine
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+ - num_epochs: 8
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.11 | 1.0 | 24 | 0.4032 | 0.8991 | 0.9040 | 0.8991 | 0.8980 |
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+ | 0.0824 | 2.0 | 48 | 0.4500 | 0.8853 | 0.8806 | 0.8874 | 0.8810 |
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+ | 0.0901 | 3.0 | 72 | 0.4908 | 0.8716 | 0.8809 | 0.8576 | 0.8653 |
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+ | 0.0554 | 4.0 | 96 | 0.4473 | 0.8991 | 0.9059 | 0.8943 | 0.8984 |
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+ | 0.0612 | 5.0 | 120 | 0.4675 | 0.8807 | 0.8867 | 0.8723 | 0.8766 |
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+ | 0.0508 | 6.0 | 144 | 0.4011 | 0.9220 | 0.9228 | 0.9191 | 0.9203 |
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+ | 0.0513 | 7.0 | 168 | 0.4161 | 0.9083 | 0.9049 | 0.9098 | 0.9070 |
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+ | 0.049 | 8.0 | 192 | 0.4210 | 0.9083 | 0.9076 | 0.9099 | 0.9085 |
 
 
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  ### Framework versions
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