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dtorber
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bert-base-cased

Text Classification
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bert
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  1. README.md +18 -16
  2. model.safetensors +1 -1
  3. runs/Apr14_22-00-35_tardis/events.out.tfevents.1713126774.tardis.129935.1 +3 -0
README.md CHANGED
@@ -18,14 +18,14 @@ 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-cased](https://huggingface.co/google-bert/bert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3688
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- - F1 Macro: 0.9065
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- - F1: 0.9385
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- - F1 Neg: 0.8745
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- - Acc: 0.9175
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- - Prec: 0.9403
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- - Recall: 0.9368
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- - Mcc: 0.8131
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  ## Model description
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@@ -51,20 +51,22 @@ The following hyperparameters were used during training:
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  - distributed_type: multi-GPU
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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: 7
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 | F1 Neg | Acc | Prec | Recall | Mcc |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:------:|:------:|
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- | 0.2307 | 1.0 | 1647 | 0.3575 | 0.9168 | 0.9386 | 0.8949 | 0.9225 | 0.9518 | 0.9258 | 0.8342 |
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- | 0.0661 | 2.0 | 3294 | 0.6221 | 0.8878 | 0.9248 | 0.8507 | 0.9 | 0.8913 | 0.9609 | 0.7811 |
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- | 0.0334 | 3.0 | 4941 | 0.8234 | 0.8964 | 0.9215 | 0.8713 | 0.9025 | 0.9502 | 0.8945 | 0.7956 |
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- | 0.0209 | 4.0 | 6588 | 0.7564 | 0.9008 | 0.9310 | 0.8705 | 0.91 | 0.9135 | 0.9492 | 0.8029 |
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- | 0.0104 | 5.0 | 8235 | 0.8753 | 0.8984 | 0.9243 | 0.8725 | 0.905 | 0.9431 | 0.9062 | 0.7981 |
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- | 0.0075 | 6.0 | 9882 | 0.8349 | 0.9109 | 0.9352 | 0.8866 | 0.9175 | 0.9407 | 0.9297 | 0.8219 |
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- | 0.0 | 7.0 | 11529 | 0.8219 | 0.9160 | 0.9393 | 0.8927 | 0.9225 | 0.9412 | 0.9375 | 0.8321 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4653
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+ - F1 Macro: 0.9023
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+ - F1: 0.9375
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+ - F1 Neg: 0.8672
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+ - Acc: 0.915
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+ - Prec: 0.9273
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+ - Recall: 0.9480
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+ - Mcc: 0.8052
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  ## Model description
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  - distributed_type: multi-GPU
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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: 9
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 | F1 Neg | Acc | Prec | Recall | Mcc |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:------:|:------:|
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+ | 0.2424 | 1.0 | 1647 | 0.3973 | 0.9023 | 0.9297 | 0.875 | 0.91 | 0.9297 | 0.9297 | 0.8047 |
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+ | 0.0939 | 2.0 | 3294 | 0.5307 | 0.9118 | 0.9387 | 0.8849 | 0.92 | 0.9211 | 0.9570 | 0.8250 |
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+ | 0.0318 | 3.0 | 4941 | 0.7560 | 0.8995 | 0.9279 | 0.8711 | 0.9075 | 0.9261 | 0.9297 | 0.7990 |
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+ | 0.0288 | 4.0 | 6588 | 0.8456 | 0.8944 | 0.9237 | 0.8651 | 0.9025 | 0.9255 | 0.9219 | 0.7887 |
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+ | 0.0177 | 5.0 | 8235 | 0.7699 | 0.8966 | 0.9261 | 0.8671 | 0.905 | 0.9225 | 0.9297 | 0.7933 |
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+ | 0.0081 | 6.0 | 9882 | 0.7886 | 0.9088 | 0.9325 | 0.8851 | 0.915 | 0.9476 | 0.9180 | 0.8185 |
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+ | 0.0053 | 7.0 | 11529 | 0.9472 | 0.8961 | 0.9218 | 0.8704 | 0.9025 | 0.9465 | 0.8984 | 0.7944 |
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+ | 0.003 | 8.0 | 13176 | 0.9317 | 0.9026 | 0.9294 | 0.8759 | 0.91 | 0.9331 | 0.9258 | 0.8053 |
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+ | 0.0 | 9.0 | 14823 | 0.9530 | 0.9026 | 0.9294 | 0.8759 | 0.91 | 0.9331 | 0.9258 | 0.8053 |
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  ### Framework versions
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