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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: albert/albert-base-v2
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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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+ - name: albert-imdb
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+ results: []
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+ ---
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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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+
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+ # albert-imdb
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+
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+ This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1801
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+ - Accuracy: 0.9488
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 24
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+ - eval_batch_size: 24
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 2
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.2322 | 0.4997 | 833 | 0.1948 | 0.9306 |
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+ | 0.1189 | 0.9994 | 1666 | 0.2103 | 0.9341 |
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+ | 0.1868 | 1.4991 | 2499 | 0.1806 | 0.9437 |
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+ | 0.1485 | 1.9988 | 3332 | 0.1801 | 0.9488 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 5.0.0
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+ - Pytorch 2.10.0+cu128
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+ - Datasets 4.0.0
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+ - Tokenizers 0.22.2
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+ {
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+ "add_prefix_space": true,
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+ "backend": "tokenizers",
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+ "bos_token": "[CLS]",
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+ "cls_token": "[CLS]",
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+ "do_lower_case": true,
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+ "tokenizer_class": "AlbertTokenizer",
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+ }