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End of training

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  1. README.md +14 -12
  2. model.safetensors +1 -1
README.md CHANGED
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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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  - generated_from_trainer
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  metrics:
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  - precision
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  - recall
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  model-index:
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- - name: bert-base-multilingual-cased-intent-booking
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- # bert-base-multilingual-cased-intent-booking
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.4853
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- - Accuracy: 0.6306
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- - F1: 0.5865
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- - Precision: 0.7935
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- - Recall: 0.6306
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  ## Model description
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@@ -57,9 +57,11 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 2.1881 | 1.0 | 65 | 1.4477 | 0.6937 | 0.6596 | 0.8102 | 0.6937 |
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- | 0.7415 | 2.0 | 130 | 0.3115 | 0.9144 | 0.9140 | 0.9178 | 0.9144 |
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- | 0.2674 | 3.0 | 195 | 0.2847 | 0.9324 | 0.9319 | 0.9393 | 0.9324 |
 
 
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  ### Framework versions
 
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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: Geotrend/bert-base-th-cased
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  - precision
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  - recall
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  model-index:
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+ - name: bert-base-th-cased-intent-booking
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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+ # bert-base-th-cased-intent-booking
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+ This model is a fine-tuned version of [Geotrend/bert-base-th-cased](https://huggingface.co/Geotrend/bert-base-th-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3126
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+ - Accuracy: 0.9144
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+ - F1: 0.9133
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+ - Precision: 0.9257
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+ - Recall: 0.9144
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 1.9427 | 1.0 | 65 | 0.7129 | 0.8964 | 0.8947 | 0.9055 | 0.8964 |
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+ | 0.5012 | 2.0 | 130 | 0.2128 | 0.9505 | 0.9501 | 0.9552 | 0.9505 |
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+ | 0.2135 | 3.0 | 195 | 0.4644 | 0.8829 | 0.8812 | 0.9208 | 0.8829 |
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+ | 0.1301 | 4.0 | 260 | 0.1812 | 0.9459 | 0.9463 | 0.9543 | 0.9459 |
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+ | 0.0785 | 5.0 | 325 | 0.2287 | 0.9459 | 0.9462 | 0.9517 | 0.9459 |
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  ### Framework versions
model.safetensors CHANGED
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