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Venkatesh4342
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distilbert-helpdesk-sentiment

Text Classification
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distilbert
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Training complete!

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  1. README.md +12 -9
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -17,7 +17,7 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2569
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  - Accuracy: 0.9417
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  ## Model description
@@ -43,19 +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: 5
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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 | 0.68 | 100 | 0.3261 | 0.8932 |
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- | No log | 1.35 | 200 | 0.3162 | 0.9029 |
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- | No log | 2.03 | 300 | 0.3394 | 0.9029 |
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- | No log | 2.7 | 400 | 0.3297 | 0.9126 |
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- | No log | 3.38 | 500 | 0.3406 | 0.9029 |
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- | 0.2652 | 4.05 | 600 | 0.3079 | 0.9320 |
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- | 0.2652 | 4.73 | 700 | 0.2569 | 0.9417 |
 
 
 
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  ### Framework versions
 
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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: 0.3008
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  - Accuracy: 0.9417
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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: 7
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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 | 0.68 | 100 | 0.3234 | 0.8932 |
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+ | No log | 1.35 | 200 | 0.3211 | 0.9029 |
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+ | No log | 2.03 | 300 | 0.3265 | 0.9126 |
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+ | No log | 2.7 | 400 | 0.3553 | 0.9126 |
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+ | No log | 3.38 | 500 | 0.3894 | 0.9223 |
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+ | 0.2663 | 4.05 | 600 | 0.3379 | 0.9223 |
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+ | 0.2663 | 4.73 | 700 | 0.2877 | 0.9320 |
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+ | 0.2663 | 5.41 | 800 | 0.3072 | 0.9417 |
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+ | 0.2663 | 6.08 | 900 | 0.2992 | 0.9320 |
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+ | 0.2663 | 6.76 | 1000 | 0.3008 | 0.9417 |
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  ### Framework versions
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