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doyoungkim
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bert-base-uncased-finetuned-sst2

Text Classification
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bert
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doyoungkim commited on
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add model

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Files changed (7) hide show
  1. README.md +9 -9
  2. config.json +1 -1
  3. pytorch_model.bin +1 -1
  4. runs/Aug11_19-02-36_c664d75a2386/1628708592.6405756/events.out.tfevents.1628708592.c664d75a2386.65.1 +3 -0
  5. runs/Aug11_19-02-36_c664d75a2386/events.out.tfevents.1628708592.c664d75a2386.65.0 +3 -0
  6. runs/Aug11_19-02-36_c664d75a2386/events.out.tfevents.1628711572.c664d75a2386.65.2 +3 -0
  7. 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: 0.9357798165137615
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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: 0.4175
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- - Accuracy: 0.9358
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  ## Model description
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@@ -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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- | 0.178 | 1.0 | 4210 | 0.3340 | 0.9037 |
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- | 0.1246 | 2.0 | 8420 | 0.3303 | 0.9186 |
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- | 0.0756 | 3.0 | 12630 | 0.3180 | 0.9289 |
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- | 0.0663 | 4.0 | 16840 | 0.3218 | 0.9323 |
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- | 0.0389 | 5.0 | 21050 | 0.4175 | 0.9358 |
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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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  metric:
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  name: Accuracy
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  type: accuracy
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+ value: 0.9277522935779816
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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: 0.3194
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+ - Accuracy: 0.9278
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.1803 | 1.0 | 4210 | 0.3157 | 0.9117 |
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+ | 0.1249 | 2.0 | 8420 | 0.3171 | 0.9209 |
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+ | 0.0803 | 3.0 | 12630 | 0.3355 | 0.9232 |
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+ | 0.0699 | 4.0 | 16840 | 0.3194 | 0.9278 |
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+ | 0.0371 | 5.0 | 21050 | 0.3965 | 0.9266 |
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  ### Framework versions
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+ - Transformers 4.9.2
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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
config.json CHANGED
@@ -20,7 +20,7 @@
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  "pretrained_model_name_or_path": "bert-base-uncased",
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  "problem_type": "single_label_classification",
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  "torch_dtype": "float32",
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- "transformers_version": "4.9.1",
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  "type_vocab_size": 2,
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  "use_cache": true,
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  "vocab_size": 30522
 
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  "pretrained_model_name_or_path": "bert-base-uncased",
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  "problem_type": "single_label_classification",
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  "torch_dtype": "float32",
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+ "transformers_version": "4.9.2",
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  "type_vocab_size": 2,
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  "use_cache": true,
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  "vocab_size": 30522
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