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fine-tuned-bert-base-uncased-swag

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End of training

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  1. README.md +9 -11
  2. model.safetensors +1 -1
  3. tokenizer.json +6 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -3,8 +3,6 @@ license: apache-2.0
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  base_model: bert-base-uncased
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  tags:
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  - generated_from_trainer
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- datasets:
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- - swag
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  metrics:
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  - accuracy
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  model-index:
@@ -17,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # fine-tuned-bert-base-uncased-swag
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- This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the swag dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5270
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- - Accuracy: 0.8139
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  ## Model description
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@@ -51,15 +49,15 @@ 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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- | 0.7707 | 1.0 | 1150 | 0.5461 | 0.7915 |
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- | 0.5848 | 2.0 | 2300 | 0.4954 | 0.8093 |
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- | 0.443 | 3.0 | 3450 | 0.5004 | 0.8132 |
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- | 0.3663 | 4.0 | 4600 | 0.5270 | 0.8139 |
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  ### Framework versions
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  - Transformers 4.41.2
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- - Pytorch 2.3.1+cu121
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- - Datasets 2.19.2
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  - Tokenizers 0.19.1
 
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  base_model: bert-base-uncased
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  tags:
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  - generated_from_trainer
 
 
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  metrics:
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  - accuracy
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  model-index:
 
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  # fine-tuned-bert-base-uncased-swag
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5259
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+ - Accuracy: 0.8134
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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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+ | 0.7736 | 1.0 | 1150 | 0.5534 | 0.7911 |
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+ | 0.5913 | 2.0 | 2300 | 0.5009 | 0.8086 |
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+ | 0.4462 | 3.0 | 3450 | 0.5014 | 0.8122 |
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+ | 0.3695 | 4.0 | 4600 | 0.5259 | 0.8134 |
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  ### Framework versions
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  - Transformers 4.41.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.20.0
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  - Tokenizers 0.19.1
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