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dtorber
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bertweet-base

Text Classification
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  1. README.md +16 -19
  2. runs/Apr06_11-17-44_tardis/events.out.tfevents.1712395069.tardis.2343.4 +2 -2
README.md CHANGED
@@ -17,14 +17,14 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7685
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- - F1 Macro: 0.8269
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- - F1: 0.8697
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- - F1 Neg: 0.7841
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- - Acc: 0.8375
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- - Prec: 0.8930
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- - Recall: 0.8477
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- - Mcc: 0.6558
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 8
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- - eval_batch_size: 8
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  - seed: 42
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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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- | 0.6468 | 1.0 | 592 | 0.5371 | 0.7329 | 0.8451 | 0.6207 | 0.78 | 0.7692 | 0.9375 | 0.5069 |
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- | 0.454 | 2.0 | 1184 | 0.5912 | 0.7849 | 0.8419 | 0.7279 | 0.8 | 0.852 | 0.8320 | 0.5702 |
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- | 0.4138 | 3.0 | 1776 | 0.6924 | 0.7853 | 0.8685 | 0.7020 | 0.8175 | 0.8060 | 0.9414 | 0.5951 |
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- | 0.3396 | 4.0 | 2368 | 0.7403 | 0.8233 | 0.8577 | 0.7888 | 0.83 | 0.9234 | 0.8008 | 0.6594 |
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- | 0.3215 | 5.0 | 2960 | 0.7685 | 0.8269 | 0.8697 | 0.7841 | 0.8375 | 0.8930 | 0.8477 | 0.6558 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6568
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+ - F1 Macro: 0.3902
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+ - F1: 0.7805
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+ - F1 Neg: 0.0
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+ - Acc: 0.64
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+ - Prec: 0.64
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+ - Recall: 1.0
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+ - Mcc: 0.0
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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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: 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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+ | No log | 1.0 | 10 | 0.7766 | 0.3902 | 0.7805 | 0.0 | 0.64 | 0.64 | 1.0 | 0.0 |
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+ | No log | 2.0 | 20 | 0.6608 | 0.3902 | 0.7805 | 0.0 | 0.64 | 0.64 | 1.0 | 0.0 |
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+ | No log | 3.0 | 30 | 0.6568 | 0.3902 | 0.7805 | 0.0 | 0.64 | 0.64 | 1.0 | 0.0 |
 
 
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  ### Framework versions
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