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distilbert-base-uncased-finetuned-imdb

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  1. README.md +8 -8
  2. runs/Feb09_02-25-40_pop-os/events.out.tfevents.1739064353.pop-os.177455.0 +2 -2
  3. runs/Feb09_02-25-40_pop-os/events.out.tfevents.1739065959.pop-os.177455.1 +3 -0
README.md CHANGED
@@ -16,8 +16,8 @@ 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: 2.3282
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- - Model Preparation Time: 0.0022
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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: 4
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- - eval_batch_size: 4
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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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  | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time |
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  |:-------------:|:-----:|:----:|:---------------:|:----------------------:|
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- | No log | 1.0 | 1522 | 2.7092 | 0.0022 |
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- | 3.0854 | 2.0 | 3044 | 2.3807 | 0.0022 |
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- | 3.0854 | 3.0 | 4566 | 2.3339 | 0.0022 |
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  ### Framework versions
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  - Transformers 4.47.1
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- - Pytorch 2.5.1+cu124
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  - Datasets 3.2.0
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  - Tokenizers 0.21.0
 
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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: 2.4671
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+ - Model Preparation Time: 0.0017
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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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  | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time |
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  |:-------------:|:-----:|:----:|:---------------:|:----------------------:|
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+ | 2.6493 | 1.0 | 625 | 2.4796 | 0.0017 |
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+ | 2.5272 | 2.0 | 1250 | 2.4307 | 0.0017 |
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+ | 2.4737 | 3.0 | 1875 | 2.4012 | 0.0017 |
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  ### Framework versions
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  - Transformers 4.47.1
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+ - Pytorch 2.5.0+cu124
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  - Datasets 3.2.0
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  - Tokenizers 0.21.0
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