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dtorber
/
bertweet-base

Text Classification
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Safetensors
roberta
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  1. README.md +16 -17
  2. model.safetensors +1 -1
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: 0.5822
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- - F1 Macro: 0.7750
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- - F1: 0.8571
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- - F1 Neg: 0.6929
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- - Acc: 0.805
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- - Prec: 0.8069
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- - Recall: 0.9141
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- - Mcc: 0.5646
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  ## Model description
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@@ -47,7 +47,6 @@ The following hyperparameters were used during training:
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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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  | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 | F1 Neg | Acc | Prec | Recall | Mcc |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:------:|:------:|
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- | 0.6482 | 1.0 | 600 | 0.5610 | 0.6822 | 0.8022 | 0.5622 | 0.7275 | 0.7492 | 0.8633 | 0.3812 |
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- | 0.5567 | 2.0 | 1200 | 0.5125 | 0.7382 | 0.8364 | 0.64 | 0.775 | 0.7823 | 0.8984 | 0.4938 |
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- | 0.4549 | 3.0 | 1800 | 0.6164 | 0.7195 | 0.7588 | 0.6802 | 0.725 | 0.865 | 0.6758 | 0.4688 |
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- | 0.4021 | 4.0 | 2400 | 0.5785 | 0.7344 | 0.7875 | 0.6812 | 0.745 | 0.8438 | 0.7383 | 0.4789 |
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- | 0.3159 | 5.0 | 3000 | 0.5822 | 0.7750 | 0.8571 | 0.6929 | 0.805 | 0.8069 | 0.9141 | 0.5646 |
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  ### Framework versions
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- - Transformers 4.38.2
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- - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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- - Tokenizers 0.15.2
 
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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: 0.6796
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+ - F1 Macro: 0.8476
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+ - F1: 0.8811
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+ - F1 Neg: 0.8141
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+ - Acc: 0.855
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+ - Prec: 0.9267
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+ - Recall: 0.8398
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+ - Mcc: 0.7020
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  ## Model description
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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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  - 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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  | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 | F1 Neg | Acc | Prec | Recall | Mcc |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:------:|:------:|
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+ | 0.6221 | 1.0 | 1161 | 0.5233 | 0.7216 | 0.8315 | 0.6116 | 0.765 | 0.7682 | 0.9062 | 0.4689 |
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+ | 0.4332 | 2.0 | 2322 | 0.4843 | 0.7862 | 0.8680 | 0.7045 | 0.8175 | 0.8081 | 0.9375 | 0.5946 |
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+ | 0.3714 | 3.0 | 3483 | 0.5872 | 0.8405 | 0.8963 | 0.7846 | 0.86 | 0.8521 | 0.9453 | 0.6914 |
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+ | 0.2856 | 4.0 | 4644 | 0.5511 | 0.8589 | 0.8984 | 0.8194 | 0.87 | 0.8984 | 0.8984 | 0.7179 |
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+ | 0.2199 | 5.0 | 5805 | 0.6796 | 0.8476 | 0.8811 | 0.8141 | 0.855 | 0.9267 | 0.8398 | 0.7020 |
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  ### Framework versions
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+ - Transformers 4.40.1
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+ - Pytorch 2.3.0+cu121
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  - Datasets 2.18.0
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+ - Tokenizers 0.19.1
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