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bert-base-uncased-finetuned-sst2

Text Classification
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bert
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add model

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Files changed (6) hide show
  1. README.md +12 -12
  2. pytorch_model.bin +2 -2
  3. runs/Aug04_12-31-15_c221d399a0d3/1628080320.3767972/events.out.tfevents.1628080320.c221d399a0d3.61.1 +3 -0
  4. runs/Aug04_12-31-15_c221d399a0d3/events.out.tfevents.1628080320.c221d399a0d3.61.0 +3 -0
  5. runs/Aug04_12-31-15_c221d399a0d3/events.out.tfevents.1628083289.c221d399a0d3.61.2 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -16,7 +16,7 @@ model_index:
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  metric:
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  name: Accuracy
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  type: accuracy
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- value: 0.9231651376146789
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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
@@ -26,8 +26,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3905
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- - Accuracy: 0.9232
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  ## Model description
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@@ -47,8 +47,8 @@ More information needed
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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: 32
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- - eval_batch_size: 32
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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
@@ -58,16 +58,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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- | 0.3915 | 1.0 | 2105 | 0.3969 | 0.9140 |
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- | 0.3667 | 2.0 | 4210 | 0.3936 | 0.9174 |
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- | 0.3609 | 3.0 | 6315 | 0.3913 | 0.9209 |
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- | 0.3518 | 4.0 | 8420 | 0.3905 | 0.9232 |
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- | 0.3467 | 5.0 | 10525 | 0.3923 | 0.9186 |
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  ### Framework versions
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  - Transformers 4.9.1
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- - Pytorch 1.8.1
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  - Datasets 1.11.0
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- - Tokenizers 0.10.1
 
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  metric:
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  name: Accuracy
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  type: accuracy
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+ value: 0.9197247706422018
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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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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3926
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+ - Accuracy: 0.9197
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.3972 | 1.0 | 4210 | 0.4020 | 0.9071 |
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+ | 0.3718 | 2.0 | 8420 | 0.4021 | 0.9083 |
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+ | 0.3548 | 3.0 | 12630 | 0.3970 | 0.9128 |
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+ | 0.3584 | 4.0 | 16840 | 0.3926 | 0.9197 |
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+ | 0.3509 | 5.0 | 21050 | 0.3966 | 0.9163 |
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  ### Framework versions
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  - Transformers 4.9.1
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+ - Pytorch 1.9.0+cu102
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  - Datasets 1.11.0
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+ - Tokenizers 0.10.3
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