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distilbert-base-uncased-finetuned-imdb

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End of training

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  1. README.md +8 -10
  2. runs/Dec10_14-48-22_bogon/events.out.tfevents.1733813323.bogon.36640.2 +2 -2
  3. runs/Dec10_14-48-22_bogon/events.out.tfevents.1733813720.bogon.36640.3 +3 -0
README.md CHANGED
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  ---
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  library_name: transformers
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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
@@ -16,8 +15,8 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.4886
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- - Model Preparation Time: 0.0007
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  ## Model description
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@@ -43,20 +42,19 @@ The following hyperparameters were used during training:
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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: 3.0
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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 | Model Preparation Time |
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  |:-------------:|:-----:|:----:|:---------------:|:----------------------:|
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- | 2.6843 | 1.0 | 157 | 2.4970 | 0.0007 |
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- | 2.5869 | 2.0 | 314 | 2.4490 | 0.0007 |
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- | 2.5266 | 3.0 | 471 | 2.4825 | 0.0007 |
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  ### Framework versions
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- - Transformers 4.46.2
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- - Pytorch 2.5.1+cu124
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  - Datasets 3.1.0
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- - Tokenizers 0.20.1
 
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  ---
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  library_name: transformers
 
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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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  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: 2.4880
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+ - Model Preparation Time: 0.0009
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  ## Model description
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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: 3.0
 
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time |
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  |:-------------:|:-----:|:----:|:---------------:|:----------------------:|
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+ | 2.6548 | 1.0 | 157 | 2.4900 | 0.0009 |
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+ | 2.5814 | 2.0 | 314 | 2.4454 | 0.0009 |
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+ | 2.5231 | 3.0 | 471 | 2.4799 | 0.0009 |
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  ### Framework versions
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+ - Transformers 4.47.0
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+ - Pytorch 2.5.1
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  - Datasets 3.1.0
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+ - Tokenizers 0.21.0
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