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Dc-4nderson
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soulprint_classifier

Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
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Dc-4nderson commited on
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Dc-4nderson/soulprint-classification2

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  1. README.md +10 -8
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -16,7 +16,7 @@ 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: 0.0714
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 0.6748 | 1.0 | 125 | 0.4952 |
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- | 0.144 | 2.0 | 250 | 0.1071 |
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- | 0.0957 | 3.0 | 375 | 0.0714 |
 
 
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  ### Framework versions
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  - Transformers 4.52.4
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  - Pytorch 2.6.0+cu124
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  - Datasets 2.14.4
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- - Tokenizers 0.21.1
 
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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: 0.0051
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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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 |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.1398 | 1.0 | 249 | 0.0834 |
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+ | 0.0219 | 2.0 | 498 | 0.0146 |
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+ | 0.0121 | 3.0 | 747 | 0.0078 |
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+ | 0.008 | 4.0 | 996 | 0.0057 |
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+ | 0.0084 | 5.0 | 1245 | 0.0051 |
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  ### Framework versions
 
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  - Transformers 4.52.4
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  - Pytorch 2.6.0+cu124
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  - Datasets 2.14.4
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+ - Tokenizers 0.21.2
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