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LogischeIP
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SentimentT2

Text Classification
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Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
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End of training

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  1. README.md +17 -14
  2. model.safetensors +1 -1
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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: 0.4572
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- - Accuracy: 0.8168
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- - F1: 0.8066
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- - Auc Roc: 0.9030
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- - Log Loss: 0.4572
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  ## Model description
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@@ -41,23 +41,26 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 5e-05
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- - train_batch_size: 32
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  - eval_batch_size: 20
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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 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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- | 0.6676 | 1.0 | 26 | 0.5624 | 0.7330 | 0.7692 | 0.8710 | 0.5624 |
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- | 0.4428 | 2.0 | 52 | 0.4274 | 0.8115 | 0.8065 | 0.8901 | 0.4274 |
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- | 0.2698 | 3.0 | 78 | 0.4124 | 0.8168 | 0.8148 | 0.9091 | 0.4124 |
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- | 0.1714 | 4.0 | 104 | 0.4655 | 0.8115 | 0.8105 | 0.8991 | 0.4655 |
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- | 0.1088 | 5.0 | 130 | 0.4572 | 0.8168 | 0.8066 | 0.9030 | 0.4572 |
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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: 0.3310
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+ - Accuracy: 0.8557
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+ - F1: 0.8589
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+ - Auc Roc: 0.9323
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+ - Log Loss: 0.3310
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 16
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  - eval_batch_size: 20
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  - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 32
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 4
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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 | Accuracy | F1 | Auc Roc | Log Loss |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-------:|:--------:|
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+ | 0.6957 | 1.0 | 101 | 0.6817 | 0.6766 | 0.7085 | 0.7441 | 0.6817 |
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+ | 0.6144 | 2.0 | 203 | 0.4599 | 0.8234 | 0.8360 | 0.9071 | 0.4599 |
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+ | 0.4133 | 3.0 | 304 | 0.3519 | 0.8570 | 0.8578 | 0.9275 | 0.3519 |
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+ | 0.3316 | 3.98 | 404 | 0.3310 | 0.8557 | 0.8589 | 0.9323 | 0.3310 |
 
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  ### Framework versions
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