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ericNguyen0132
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2ndDepRoBERTa-v3

Text Classification
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roberta
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  1. README.md +10 -10
  2. pytorch_model.bin +1 -1
  3. runs/Jul13_02-06-57_718cb121b3f3/events.out.tfevents.1689214472.718cb121b3f3.1839.0 +2 -2
README.md CHANGED
@@ -16,9 +16,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [rafalposwiata/deproberta-large-v1](https://huggingface.co/rafalposwiata/deproberta-large-v1) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6977
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- - Accuracy: 0.8183
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- - F1: 0.8915
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-06
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | No log | 1.0 | 469 | 0.3739 | 0.8633 | 0.9238 |
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- | 0.5138 | 2.0 | 938 | 0.3603 | 0.8617 | 0.9225 |
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- | 0.3776 | 3.0 | 1407 | 0.4346 | 0.8433 | 0.9080 |
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- | 0.3597 | 4.0 | 1876 | 0.5701 | 0.8467 | 0.9110 |
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- | 0.2949 | 5.0 | 2345 | 0.6977 | 0.8183 | 0.8915 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [rafalposwiata/deproberta-large-v1](https://huggingface.co/rafalposwiata/deproberta-large-v1) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9025
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+ - Accuracy: 0.83
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+ - F1: 0.8988
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-06
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.5962 | 1.0 | 938 | 0.5780 | 0.86 | 0.9209 |
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+ | 0.4972 | 2.0 | 1876 | 0.5820 | 0.8567 | 0.9184 |
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+ | 0.4751 | 3.0 | 2814 | 0.6757 | 0.8483 | 0.9112 |
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+ | 0.3889 | 4.0 | 3752 | 0.8244 | 0.8367 | 0.9034 |
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+ | 0.3363 | 5.0 | 4690 | 0.9025 | 0.83 | 0.8988 |
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  ### Framework versions
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