End of training
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README.md
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---
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license: apache-2.0
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base_model: albert-base-v2
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tags:
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- generated_from_trainer
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datasets:
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- imdb
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model-index:
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- name: albert_base_v2_imdb
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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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# albert_base_v2_imdb
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This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the imdb dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 0.3031
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- eval_accuracy: 0.898
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- eval_runtime: 21.4873
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- eval_samples_per_second: 46.539
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- eval_steps_per_second: 2.932
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- epoch: 4.08
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- step: 399
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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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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- gradient_accumulation_steps: 16
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- total_train_batch_size: 256
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 10
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- mixed_precision_training: Native AMP
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### Framework versions
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- Transformers 4.35.0
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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model.safetensors
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