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End of training

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: xlnet-base-cased
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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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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: IMDB-XLNet-CLSModel_v1
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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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+ # IMDB-XLNet-CLSModel_v1
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+
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+ This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6942
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+ - Accuracy: 0.5014
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+ - F1: 0.3339
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+ - Precision: 0.2507
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+ - Recall: 0.5
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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: 0.0003
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+ - train_batch_size: 32
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+ - eval_batch_size: 64
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+ - seed: 42
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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_steps: 100
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+ - num_epochs: 1
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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 | F1 | Precision | Recall |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | No log | 0.3836 | 300 | 0.7060 | 0.5014 | 0.3339 | 0.2507 | 0.5 |
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+ | 0.6617 | 0.7673 | 600 | 0.6942 | 0.5014 | 0.3339 | 0.2507 | 0.5 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.1.2
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
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