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my_awesome_model

Text Classification
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distilbert
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End of training

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  1. README.md +13 -5
  2. model.safetensors +1 -1
  3. runs/Mar26_13-47-53_423a215ba150/events.out.tfevents.1711460874.423a215ba150.413.4 +2 -2
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/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: 0.3147
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- - Accuracy: 0.8799
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  ## Model description
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@@ -43,14 +43,22 @@ The following hyperparameters were used during training:
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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: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 192 | 0.3343 | 0.8786 |
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- | No log | 2.0 | 384 | 0.3147 | 0.8799 |
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/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: 0.3764
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+ - Accuracy: 0.8616
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  ## Model description
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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: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 192 | 0.3510 | 0.8629 |
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+ | No log | 2.0 | 384 | 0.3658 | 0.8629 |
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+ | 0.2898 | 3.0 | 576 | 0.3585 | 0.8564 |
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+ | 0.2898 | 4.0 | 768 | 0.3760 | 0.8629 |
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+ | 0.2898 | 5.0 | 960 | 0.3911 | 0.8629 |
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+ | 0.285 | 6.0 | 1152 | 0.3838 | 0.8629 |
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+ | 0.285 | 7.0 | 1344 | 0.3728 | 0.8629 |
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+ | 0.2806 | 8.0 | 1536 | 0.3725 | 0.8616 |
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+ | 0.2806 | 9.0 | 1728 | 0.3731 | 0.8629 |
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+ | 0.2806 | 10.0 | 1920 | 0.3764 | 0.8616 |
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  ### Framework versions
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