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bert-base-uncased-finetuned-sst2

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fine tuned, probability as logits

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Files changed (5) hide show
  1. README.md +9 -9
  2. config.json +1 -1
  3. pytorch_model.bin +1 -1
  4. tokenizer.json +0 -0
  5. 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: 0.930045871559633
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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: 0.2485
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- - Accuracy: 0.9300
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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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- | 0.1662 | 1.0 | 2105 | 0.2485 | 0.9300 |
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- | 0.1102 | 2.0 | 4210 | 0.2777 | 0.9266 |
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- | 0.0835 | 3.0 | 6315 | 0.3368 | 0.9232 |
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- | 0.0529 | 4.0 | 8420 | 0.3310 | 0.9255 |
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- | 0.035 | 5.0 | 10525 | 0.3855 | 0.9278 |
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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: 0.926605504587156
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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: 0.2716
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+ - Accuracy: 0.9266
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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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+ | 0.1666 | 1.0 | 2105 | 0.2403 | 0.9232 |
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+ | 0.1122 | 2.0 | 4210 | 0.2716 | 0.9266 |
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+ | 0.0852 | 3.0 | 6315 | 0.3150 | 0.9232 |
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+ | 0.056 | 4.0 | 8420 | 0.3209 | 0.9163 |
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+ | 0.0344 | 5.0 | 10525 | 0.3740 | 0.9243 |
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  ### Framework versions
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+ - Transformers 4.9.2
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  - Pytorch 1.8.1
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  - Datasets 1.11.0
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  - Tokenizers 0.10.1
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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tokenizer.json CHANGED
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