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LogischeIP
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SentimentT2

Text Classification
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Safetensors
distilbert
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End of training

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  1. README.md +12 -16
  2. model.safetensors +1 -1
  3. runs/Jan17_23-22-16_a95ba52b8e14/events.out.tfevents.1705533737.a95ba52b8e14.206.28 +3 -0
  4. runs/Jan17_23-24-16_a95ba52b8e14/events.out.tfevents.1705533857.a95ba52b8e14.206.29 +3 -0
  5. runs/Jan17_23-24-33_a95ba52b8e14/events.out.tfevents.1705533874.a95ba52b8e14.206.30 +3 -0
  6. runs/Jan17_23-24-42_a95ba52b8e14/events.out.tfevents.1705533883.a95ba52b8e14.206.31 +3 -0
  7. runs/Jan17_23-24-52_a95ba52b8e14/events.out.tfevents.1705533894.a95ba52b8e14.206.32 +3 -0
  8. training_args.bin +1 -1
README.md CHANGED
@@ -18,11 +18,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5309
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- - Accuracy: 0.875
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- - F1: 0.5098
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- - Auc Roc: 0.9113
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- - Log Loss: 0.5309
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  ## Model description
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@@ -48,22 +48,18 @@ The following hyperparameters were used during training:
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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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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Auc Roc | Log Loss |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-------:|:--------:|
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- | No log | 1.0 | 13 | 0.4223 | 0.84 | 0.0 | 0.8263 | 0.4223 |
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- | No log | 2.0 | 26 | 0.3733 | 0.84 | 0.0 | 0.8826 | 0.3733 |
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- | No log | 3.0 | 39 | 0.3542 | 0.85 | 0.25 | 0.9012 | 0.3542 |
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- | No log | 4.0 | 52 | 0.2945 | 0.88 | 0.625 | 0.8955 | 0.2945 |
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- | No log | 5.0 | 65 | 0.3566 | 0.875 | 0.5283 | 0.9111 | 0.3566 |
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- | No log | 6.0 | 78 | 0.4393 | 0.865 | 0.4906 | 0.9049 | 0.4393 |
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- | No log | 7.0 | 91 | 0.4951 | 0.865 | 0.4706 | 0.9085 | 0.4951 |
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- | No log | 8.0 | 104 | 0.4460 | 0.885 | 0.6102 | 0.9057 | 0.4460 |
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- | No log | 9.0 | 117 | 0.5089 | 0.87 | 0.5000 | 0.9094 | 0.5089 |
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- | 0.1739 | 10.0 | 130 | 0.5309 | 0.875 | 0.5098 | 0.9113 | 0.5309 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5072
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+ - Accuracy: 0.8864
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+ - F1: 0.6743
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+ - Auc Roc: 0.9227
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+ - Log Loss: 0.5072
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  ## Model description
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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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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 6
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Auc Roc | Log Loss |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-------:|:--------:|
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+ | No log | 1.0 | 125 | 0.2532 | 0.8912 | 0.6495 | 0.9322 | 0.2532 |
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+ | No log | 2.0 | 250 | 0.2346 | 0.8944 | 0.6716 | 0.9370 | 0.2346 |
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+ | No log | 3.0 | 375 | 0.3353 | 0.8976 | 0.6893 | 0.9319 | 0.3353 |
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+ | No log | 4.0 | 500 | 0.4296 | 0.8864 | 0.6520 | 0.9284 | 0.4296 |
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+ | No log | 5.0 | 625 | 0.4896 | 0.8856 | 0.6603 | 0.9224 | 0.4896 |
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+ | 0.1517 | 6.0 | 750 | 0.5072 | 0.8864 | 0.6743 | 0.9227 | 0.5072 |
 
 
 
 
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  ### Framework versions
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