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QuophyDzifa
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Sentiment-Analysis-Model

Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
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  1. README.md +25 -25
  2. pytorch_model.bin +1 -1
README.md CHANGED
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  ---
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- license: mit
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- base_model: roberta-base
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  tags:
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  - generated_from_trainer
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  model-index:
@@ -13,10 +13,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # Sentiment-Analysis-Model
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- This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7057
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- - F1 Score: 0.6844
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  ## Model description
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@@ -47,26 +47,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 Score |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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- | 0.8268 | 0.5 | 500 | 0.7473 | 0.6734 |
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- | 0.792 | 1.0 | 1000 | 0.7927 | 0.6723 |
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- | 0.7531 | 1.5 | 1500 | 0.7387 | 0.6705 |
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- | 0.7527 | 2.0 | 2000 | 0.7057 | 0.6844 |
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- | 0.7302 | 2.5 | 2500 | 0.7520 | 0.6775 |
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- | 0.7355 | 3.0 | 3000 | 0.7379 | 0.6797 |
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- | 0.7245 | 3.5 | 3500 | 0.7260 | 0.6811 |
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- | 0.7383 | 4.0 | 4000 | 0.7445 | 0.6791 |
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- | 0.7271 | 4.5 | 4500 | 0.7372 | 0.6787 |
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- | 0.7306 | 5.0 | 5000 | 0.7308 | 0.6816 |
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- | 0.7259 | 5.5 | 5500 | 0.7407 | 0.6851 |
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- | 0.7286 | 6.0 | 6000 | 0.7517 | 0.6854 |
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- | 0.7515 | 6.5 | 6500 | 0.7702 | 0.6822 |
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- | 0.6996 | 7.0 | 7000 | 0.7286 | 0.6877 |
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- | 0.7067 | 7.5 | 7500 | 0.7413 | 0.6832 |
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- | 0.7195 | 8.0 | 8000 | 0.7561 | 0.6842 |
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- | 0.7041 | 8.5 | 8500 | 0.7812 | 0.6819 |
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- | 0.7329 | 9.0 | 9000 | 0.7717 | 0.6846 |
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- | 0.7046 | 9.5 | 9500 | 0.7625 | 0.6817 |
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- | 0.722 | 10.0 | 10000 | 0.7432 | 0.6897 |
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  ### Framework versions
 
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  ---
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+ license: apache-2.0
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+ base_model: distilbert-base-uncased
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  tags:
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  - generated_from_trainer
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  model-index:
 
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  # Sentiment-Analysis-Model
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6227
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+ - F1 Score: 0.7304
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 Score |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.7461 | 0.5 | 500 | 0.7528 | 0.6523 |
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+ | 0.6845 | 1.0 | 1000 | 0.6425 | 0.7132 |
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+ | 0.5729 | 1.5 | 1500 | 0.6463 | 0.7415 |
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+ | 0.5674 | 2.0 | 2000 | 0.6227 | 0.7304 |
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+ | 0.41 | 2.5 | 2500 | 0.9091 | 0.7335 |
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+ | 0.4017 | 3.0 | 3000 | 0.8304 | 0.7360 |
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+ | 0.2691 | 3.5 | 3500 | 1.2177 | 0.7202 |
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+ | 0.3128 | 4.0 | 4000 | 1.1197 | 0.7376 |
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+ | 0.197 | 4.5 | 4500 | 1.2951 | 0.7341 |
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+ | 0.1887 | 5.0 | 5000 | 1.4508 | 0.7239 |
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+ | 0.11 | 5.5 | 5500 | 1.5447 | 0.7203 |
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+ | 0.1462 | 6.0 | 6000 | 1.4909 | 0.7383 |
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+ | 0.0907 | 6.5 | 6500 | 1.4809 | 0.7332 |
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+ | 0.089 | 7.0 | 7000 | 1.7191 | 0.7244 |
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+ | 0.0613 | 7.5 | 7500 | 1.7725 | 0.7294 |
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+ | 0.0665 | 8.0 | 8000 | 1.8083 | 0.7290 |
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+ | 0.0458 | 8.5 | 8500 | 1.8297 | 0.7346 |
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+ | 0.0395 | 9.0 | 9000 | 1.8853 | 0.7304 |
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+ | 0.0287 | 9.5 | 9500 | 1.9684 | 0.7273 |
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+ | 0.0204 | 10.0 | 10000 | 1.9919 | 0.7308 |
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  ### Framework versions
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