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distilbert-base-uncased-finetuned-sst2

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  1. README.md +11 -7
  2. pytorch_model.bin +1 -1
  3. runs/Aug02_16-06-59_7fecced68ee5/1627920443.493723/events.out.tfevents.1627920443.7fecced68ee5.61.1 +3 -0
  4. runs/Aug02_16-06-59_7fecced68ee5/events.out.tfevents.1627920443.7fecced68ee5.61.0 +3 -0
  5. runs/Aug02_16-06-59_7fecced68ee5/events.out.tfevents.1627921996.7fecced68ee5.61.2 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -19,7 +19,7 @@ model_index:
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  metric:
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  name: Accuracy
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  type: accuracy
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- value: 0.9025229357798165
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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
@@ -29,8 +29,8 @@ 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 the glue dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2945
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- - Accuracy: 0.9025
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  ## Model description
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@@ -55,13 +55,17 @@ 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: 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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- | 0.1838 | 1.0 | 4210 | 0.2945 | 0.9025 |
 
 
 
 
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  ### Framework versions
 
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  metric:
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  name: Accuracy
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  type: accuracy
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+ value: 0.9151376146788991
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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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3651
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+ - Accuracy: 0.9151
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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: 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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+ | 0.1902 | 1.0 | 4210 | 0.3102 | 0.9117 |
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+ | 0.1293 | 2.0 | 8420 | 0.3672 | 0.9048 |
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+ | 0.084 | 3.0 | 12630 | 0.3651 | 0.9151 |
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+ | 0.0682 | 4.0 | 16840 | 0.3971 | 0.9037 |
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+ | 0.0438 | 5.0 | 21050 | 0.4720 | 0.9117 |
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  ### Framework versions
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