Model save
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- training_args.bin +1 -1
README.md
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# model_24
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 0.6274
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- eval_accuracy: 0.7763
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- eval_precision: 0.7757
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- eval_recall: 0.7763
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- eval_f1: 0.7759
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- eval_runtime: 42.4085
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- eval_samples_per_second: 288.739
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- eval_steps_per_second: 18.062
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- epoch: 3.0
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- step: 9186
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 1000
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- num_epochs:
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- mixed_precision_training: Native AMP
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- label_smoothing_factor: 0.03
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# model_24
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 1000
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- num_epochs: 60
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- mixed_precision_training: Native AMP
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- label_smoothing_factor: 0.03
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adapter_model.safetensors
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training_args.bin
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