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eovdedn
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bert_essay

Text Classification
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deberta-v2
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text-embeddings-inference
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eovdedn/bert_essay

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Files changed (4) hide show
  1. README.md +18 -10
  2. model.safetensors +1 -1
  3. runs/May02_15-59-05_f87be7dee12d/events.out.tfevents.1714665546.f87be7dee12d.35.1 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -6,22 +6,22 @@ tags:
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  metrics:
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  - accuracy
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  model-index:
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- - name: essay_score
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- # essay_score
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  This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/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: 0.3566
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- - Mse: 0.3566
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- - Mae: 0.4629
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- - R2: 0.6715
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- - Accuracy: 0.2789
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  ## Model description
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@@ -46,14 +46,22 @@ 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 | Mse | Mae | R2 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:--------:|
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- | 0.6508 | 1.0 | 866 | 0.4269 | 0.4269 | 0.5067 | 0.6067 | 0.2917 |
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- | 0.3457 | 2.0 | 1732 | 0.3566 | 0.3566 | 0.4629 | 0.6715 | 0.2789 |
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  metrics:
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  - accuracy
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  model-index:
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+ - name: bert_essay
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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+ # bert_essay
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  This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/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: 0.3910
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+ - Mse: 0.3910
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+ - Mae: 0.4864
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+ - R2: 0.6456
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+ - Accuracy: 0.2734
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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 | Mse | Mae | R2 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:--------:|
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+ | 0.6884 | 1.0 | 866 | 0.3664 | 0.3664 | 0.4744 | 0.6679 | 0.2812 |
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+ | 0.3801 | 2.0 | 1732 | 0.3550 | 0.3550 | 0.4630 | 0.6782 | 0.2822 |
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+ | 0.3063 | 3.0 | 2598 | 0.3723 | 0.3723 | 0.4736 | 0.6626 | 0.2761 |
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+ | 0.2386 | 4.0 | 3464 | 0.3965 | 0.3965 | 0.4895 | 0.6406 | 0.2697 |
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+ | 0.1751 | 5.0 | 4330 | 0.3718 | 0.3718 | 0.4732 | 0.6630 | 0.2754 |
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+ | 0.1335 | 6.0 | 5196 | 0.3815 | 0.3815 | 0.4793 | 0.6542 | 0.2759 |
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+ | 0.102 | 7.0 | 6062 | 0.3872 | 0.3872 | 0.4835 | 0.6490 | 0.2813 |
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+ | 0.0879 | 8.0 | 6928 | 0.3998 | 0.3998 | 0.4911 | 0.6376 | 0.2707 |
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+ | 0.0718 | 9.0 | 7794 | 0.3892 | 0.3892 | 0.4848 | 0.6472 | 0.2728 |
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+ | 0.0621 | 10.0 | 8660 | 0.3910 | 0.3910 | 0.4864 | 0.6456 | 0.2734 |
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  ### Framework versions
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