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dtorber
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bertweet-base

Text Classification
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roberta
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@@ -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: 0.7965
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- - F1 Macro: 0.8142
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- - F1: 0.8639
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- - F1 Neg: 0.7645
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- - Acc: 0.8275
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- - Prec: 0.8725
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- - Recall: 0.8555
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- - Mcc: 0.6287
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  ## Model description
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@@ -50,18 +50,16 @@ 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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- | 0.6396 | 1.0 | 614 | 0.6126 | 0.7238 | 0.7652 | 0.6824 | 0.73 | 0.8627 | 0.6875 | 0.4734 |
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- | 0.4753 | 2.0 | 1228 | 0.5095 | 0.8057 | 0.8669 | 0.7445 | 0.825 | 0.8444 | 0.8906 | 0.6138 |
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- | 0.3965 | 3.0 | 1842 | 0.7932 | 0.7358 | 0.8527 | 0.6188 | 0.7875 | 0.7664 | 0.9609 | 0.5306 |
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- | 0.3534 | 4.0 | 2456 | 0.8950 | 0.7831 | 0.8140 | 0.7522 | 0.7875 | 0.9254 | 0.7266 | 0.5975 |
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- | 0.2284 | 5.0 | 3070 | 0.7965 | 0.8142 | 0.8639 | 0.7645 | 0.8275 | 0.8725 | 0.8555 | 0.6287 |
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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: 0.5690
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+ - F1 Macro: 0.7699
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+ - F1: 0.8459
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+ - F1 Neg: 0.6940
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+ - Acc: 0.795
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+ - Prec: 0.8152
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+ - Recall: 0.8789
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+ - Mcc: 0.5446
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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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+ | 0.6752 | 1.0 | 592 | 0.6373 | 0.5685 | 0.8134 | 0.3237 | 0.7075 | 0.6873 | 0.9961 | 0.3527 |
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+ | 0.4957 | 2.0 | 1184 | 0.7489 | 0.7577 | 0.8122 | 0.7032 | 0.77 | 0.8504 | 0.7773 | 0.5205 |
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+ | 0.4233 | 3.0 | 1776 | 0.5690 | 0.7699 | 0.8459 | 0.6940 | 0.795 | 0.8152 | 0.8789 | 0.5446 |
 
 
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  ### Framework versions