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hackMIT-finetuned-sst2

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add model

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Files changed (29) hide show
  1. README.md +14 -12
  2. config.json +1 -1
  3. pytorch_model.bin +1 -1
  4. runs/Aug23_22-10-02_94aec2123ad7/1629758635.1839979/events.out.tfevents.1629758635.94aec2123ad7.79.12 +3 -0
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  29. training_args.bin +1 -1
README.md CHANGED
@@ -18,7 +18,7 @@ model_index:
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  metric:
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  name: Accuracy
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  type: accuracy
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- value: 0.7924311926605505
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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
@@ -26,10 +26,10 @@ should probably proofread and complete it, then remove this comment. -->
26
 
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  # hackMIT-finetuned-sst2
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- This model is a fine-tuned version of [Blaine-Mason/hackMIT-finetuned-sst2](https://huggingface.co/Blaine-Mason/hackMIT-finetuned-sst2) on the glue dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.5749
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- - Accuracy: 0.7924
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  ## Model description
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@@ -48,20 +48,22 @@ 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: 3.895748906373482e-06
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- - train_batch_size: 4
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  - eval_batch_size: 16
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- - seed: 26
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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 | Accuracy |
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- |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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- | 0.0785 | 1.0 | 16838 | 1.5605 | 0.7913 |
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- | 0.1208 | 2.0 | 33676 | 1.5749 | 0.7924 |
 
 
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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: 0.7912844036697247
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  ---
23
 
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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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  # hackMIT-finetuned-sst2
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+ This model is a fine-tuned version of [HackMIT/double-agent](https://huggingface.co/HackMIT/double-agent) on the glue dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0808
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+ - Accuracy: 0.7913
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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: 2.1464034066142034e-05
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+ - train_batch_size: 64
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  - eval_batch_size: 16
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+ - seed: 32
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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: 4
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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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+ | 0.069 | 1.0 | 1053 | 1.0202 | 0.7924 |
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+ | 0.0633 | 2.0 | 2106 | 1.1031 | 0.7878 |
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+ | 0.0584 | 3.0 | 3159 | 1.0870 | 0.7878 |
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+ | 0.0576 | 4.0 | 4212 | 1.0808 | 0.7913 |
67
 
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  ### Framework versions
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