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dtorber
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bert-base-cased

Text Classification
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bert
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Training in progress, epoch 1

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  1. README.md +11 -13
  2. model.safetensors +1 -1
  3. runs/Apr06_15-14-56_tardis/events.out.tfevents.1712409303.tardis.11888.0 +3 -0
  4. runs/Apr06_15-16-57_tardis/events.out.tfevents.1712409424.tardis.12350.0 +3 -0
  5. training_args.bin +1 -1
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: 0.5503
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- - F1 Macro: 0.9046
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- - F1: 0.9320
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- - F1 Neg: 0.8772
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  - Acc: 0.9125
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- - Prec: 0.9266
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- - Recall: 0.9375
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- - Mcc: 0.8094
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  ## Model description
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@@ -51,18 +51,16 @@ 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: 5
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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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- | No log | 1.0 | 455 | 0.3613 | 0.8215 | 0.8706 | 0.7724 | 0.835 | 0.8740 | 0.8672 | 0.6430 |
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- | 0.4501 | 2.0 | 910 | 0.3824 | 0.8791 | 0.9193 | 0.8390 | 0.8925 | 0.8845 | 0.9570 | 0.7643 |
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- | 0.2737 | 3.0 | 1365 | 0.4971 | 0.8770 | 0.9084 | 0.8456 | 0.885 | 0.9268 | 0.8906 | 0.7552 |
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- | 0.1573 | 4.0 | 1820 | 0.5008 | 0.8912 | 0.9222 | 0.8601 | 0.9 | 0.9186 | 0.9258 | 0.7824 |
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- | 0.0839 | 5.0 | 2275 | 0.5503 | 0.9046 | 0.9320 | 0.8772 | 0.9125 | 0.9266 | 0.9375 | 0.8094 |
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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: 0.3765
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+ - F1 Macro: 0.8988
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+ - F1: 0.9360
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+ - F1 Neg: 0.8617
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  - Acc: 0.9125
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+ - Prec: 0.9209
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+ - Recall: 0.9517
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+ - Mcc: 0.7989
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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: 3
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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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+ | 0.5022 | 1.0 | 824 | 0.4717 | 0.8752 | 0.9102 | 0.8403 | 0.885 | 0.9102 | 0.9102 | 0.7504 |
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+ | 0.3452 | 2.0 | 1648 | 0.4330 | 0.8882 | 0.9245 | 0.8519 | 0.9 | 0.8942 | 0.9570 | 0.7808 |
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+ | 0.2232 | 3.0 | 2472 | 0.5604 | 0.8652 | 0.9060 | 0.8244 | 0.8775 | 0.8906 | 0.9219 | 0.7314 |
 
 
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  ### Framework versions
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