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End of training

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  1. README.md +37 -3
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -2,6 +2,8 @@
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  base_model: neal49/distilbert-sst2-runglue
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  tags:
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  - generated_from_trainer
 
 
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  model-index:
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  - name: dnd
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  results: []
@@ -13,6 +15,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # dnd
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  This model is a fine-tuned version of [neal49/distilbert-sst2-runglue](https://huggingface.co/neal49/distilbert-sst2-runglue) on an unknown dataset.
 
 
 
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  ## Model description
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@@ -31,19 +36,48 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 1e-08
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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: 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: 1
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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 | 15 | 0.4952 | 0.8421 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  base_model: neal49/distilbert-sst2-runglue
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  tags:
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  - generated_from_trainer
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+ metrics:
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+ - accuracy
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  model-index:
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  - name: dnd
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  results: []
 
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  # dnd
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  This model is a fine-tuned version of [neal49/distilbert-sst2-runglue](https://huggingface.co/neal49/distilbert-sst2-runglue) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4907
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+ - Accuracy: 0.8246
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 2e-06
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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: 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: 30
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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 | 15 | 0.6813 | 0.5789 |
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+ | No log | 2.0 | 30 | 0.6725 | 0.5789 |
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+ | No log | 3.0 | 45 | 0.6588 | 0.6140 |
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+ | No log | 4.0 | 60 | 0.6536 | 0.6140 |
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+ | No log | 5.0 | 75 | 0.6524 | 0.6140 |
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+ | No log | 6.0 | 90 | 0.6426 | 0.6140 |
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+ | No log | 7.0 | 105 | 0.6333 | 0.6316 |
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+ | No log | 8.0 | 120 | 0.6148 | 0.6491 |
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+ | No log | 9.0 | 135 | 0.6081 | 0.6491 |
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+ | No log | 10.0 | 150 | 0.5724 | 0.7018 |
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+ | No log | 11.0 | 165 | 0.5984 | 0.6842 |
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+ | No log | 12.0 | 180 | 0.5328 | 0.7368 |
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+ | No log | 13.0 | 195 | 0.5419 | 0.7719 |
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+ | No log | 14.0 | 210 | 0.5271 | 0.7719 |
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+ | No log | 15.0 | 225 | 0.5188 | 0.7719 |
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+ | No log | 16.0 | 240 | 0.5283 | 0.7719 |
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+ | No log | 17.0 | 255 | 0.5012 | 0.7719 |
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+ | No log | 18.0 | 270 | 0.4863 | 0.7895 |
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+ | No log | 19.0 | 285 | 0.5329 | 0.7895 |
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+ | No log | 20.0 | 300 | 0.4861 | 0.8070 |
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+ | No log | 21.0 | 315 | 0.5065 | 0.8246 |
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+ | No log | 22.0 | 330 | 0.4864 | 0.8070 |
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+ | No log | 23.0 | 345 | 0.5060 | 0.8246 |
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+ | No log | 24.0 | 360 | 0.4752 | 0.8246 |
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+ | No log | 25.0 | 375 | 0.4983 | 0.8246 |
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+ | No log | 26.0 | 390 | 0.4925 | 0.8246 |
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+ | No log | 27.0 | 405 | 0.4774 | 0.8246 |
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+ | No log | 28.0 | 420 | 0.4804 | 0.8246 |
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+ | No log | 29.0 | 435 | 0.4927 | 0.8246 |
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+ | No log | 30.0 | 450 | 0.4907 | 0.8246 |
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  ### Framework versions
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