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hackMIT-finetuned-sst2

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add model

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  1. README.md +9 -20
  2. pytorch_model.bin +1 -1
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README.md CHANGED
@@ -3,8 +3,6 @@ tags:
3
  - generated_from_trainer
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  datasets:
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  - glue
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- metrics:
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- - accuracy
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  model_index:
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  - name: hackMIT-finetuned-sst2
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  results:
@@ -15,10 +13,6 @@ model_index:
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  name: glue
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  type: glue
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  args: sst2
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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
@@ -28,8 +22,13 @@ should probably proofread and complete it, then remove this comment. -->
28
 
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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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@@ -48,24 +47,14 @@ 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: 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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-
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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 |
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-
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-
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  ### Framework versions
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  - Transformers 4.9.2
 
3
  - generated_from_trainer
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  datasets:
5
  - glue
 
 
6
  model_index:
7
  - name: hackMIT-finetuned-sst2
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  results:
 
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  name: glue
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  type: glue
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  args: sst2
 
 
 
 
16
  ---
17
 
18
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
22
 
23
  This model is a fine-tuned version of [HackMIT/double-agent](https://huggingface.co/HackMIT/double-agent) on the glue dataset.
24
  It achieves the following results on the evaluation set:
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+ - eval_loss: 1.3815
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+ - eval_accuracy: 0.7867
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+ - eval_runtime: 0.4331
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+ - eval_samples_per_second: 2013.178
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+ - eval_steps_per_second: 126.978
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+ - epoch: 1.0
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+ - step: 1053
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  ## Model description
34
 
 
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
50
+ - learning_rate: 1.180110127699872e-06
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  - train_batch_size: 64
52
  - eval_batch_size: 16
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+ - seed: 14
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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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  ### Framework versions
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  - Transformers 4.9.2
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