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aadhistii
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tsel-finetune-bert-base-multilingual-cased-2k-formal-v2

Text Classification
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bert
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1 Parent(s): 9cadade

Training in progress epoch 9

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Files changed (4) hide show
  1. README.md +8 -7
  2. logs/train/events.out.tfevents.1720676383.4714aa4ab9cd.30701.0.v2 +2 -2
  3. logs/validation/events.out.tfevents.1720676519.4714aa4ab9cd.30701.1.v2 +2 -2
  4. tf_model.h5 +1 -1
README.md CHANGED
@@ -15,13 +15,13 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.0563
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- - Validation Loss: 1.0643
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- - Train Precision: 0.7141
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- - Train Recall: 0.7032
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- - Train F1: 0.7079
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- - Train Accuracy: 0.7234
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- - Epoch: 8
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  ## Model description
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@@ -56,6 +56,7 @@ The following hyperparameters were used during training:
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  | 0.1073 | 0.9961 | 0.7076 | 0.7278 | 0.7132 | 0.7261 | 6 |
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  | 0.0712 | 1.0520 | 0.7069 | 0.6980 | 0.7004 | 0.7181 | 7 |
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  | 0.0563 | 1.0643 | 0.7141 | 0.7032 | 0.7079 | 0.7234 | 8 |
 
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  ### Framework versions
 
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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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+ - Train Loss: 0.0457
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+ - Validation Loss: 1.0705
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+ - Train Precision: 0.7102
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+ - Train Recall: 0.7104
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+ - Train F1: 0.7103
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+ - Train Accuracy: 0.7207
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+ - Epoch: 9
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  ## Model description
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  | 0.1073 | 0.9961 | 0.7076 | 0.7278 | 0.7132 | 0.7261 | 6 |
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  | 0.0712 | 1.0520 | 0.7069 | 0.6980 | 0.7004 | 0.7181 | 7 |
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  | 0.0563 | 1.0643 | 0.7141 | 0.7032 | 0.7079 | 0.7234 | 8 |
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+ | 0.0457 | 1.0705 | 0.7102 | 0.7104 | 0.7103 | 0.7207 | 9 |
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  ### Framework versions
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