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Training in progress, epoch 1

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  1. README.md +4 -15
  2. model.safetensors +1 -1
  3. tokenizer.json +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -5,18 +5,16 @@ base_model: bert-base-uncased
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  tags:
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  - generated_from_trainer
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  model-index:
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- - name: roberta-base-uncased-finetuned-swag
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  results: []
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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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  should probably proofread and complete it, then remove this comment. -->
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- # roberta-base-uncased-finetuned-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: 0.5882
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  ## Model description
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@@ -36,22 +34,13 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 18
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- - eval_batch_size: 18
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - num_epochs: 3
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- ### Training results
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-
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- | Training Loss | Epoch | Step | Validation Loss |
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- |:-------------:|:-----:|:-----:|:---------------:|
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- | 0.7467 | 1.0 | 4086 | 0.5882 |
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- | 0.3706 | 2.0 | 8172 | 0.6025 |
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- | 0.1451 | 3.0 | 12258 | 0.9545 |
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-
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-
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  ### Framework versions
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  - Transformers 4.46.3
 
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  tags:
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  - generated_from_trainer
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  model-index:
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+ - name: results
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  results: []
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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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  should probably proofread and complete it, then remove this comment. -->
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+ # results
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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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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 12
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+ - eval_batch_size: 12
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - num_epochs: 3
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  ### Framework versions
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  - Transformers 4.46.3
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tokenizer.json CHANGED
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