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update model card README.md

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+ ---
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+ license: mit
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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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+ model-index:
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+ - name: rubert-tiny2_finetuned_emotion_experiment
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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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+ # rubert-tiny2_finetuned_emotion_experiment
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+
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+ This model is a fine-tuned version of [cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3947
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+ - Accuracy: 0.8616
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+ - F1: 0.8577
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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: 64
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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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+ - num_epochs: 15
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.651 | 1.0 | 54 | 0.5689 | 0.8172 | 0.8008 |
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+ | 0.5355 | 2.0 | 108 | 0.4842 | 0.8486 | 0.8349 |
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+ | 0.4561 | 3.0 | 162 | 0.4436 | 0.8590 | 0.8509 |
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+ | 0.4133 | 4.0 | 216 | 0.4203 | 0.8590 | 0.8528 |
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+ | 0.3709 | 5.0 | 270 | 0.4071 | 0.8564 | 0.8515 |
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+ | 0.3346 | 6.0 | 324 | 0.3980 | 0.8564 | 0.8529 |
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+ | 0.3153 | 7.0 | 378 | 0.3985 | 0.8590 | 0.8565 |
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+ | 0.302 | 8.0 | 432 | 0.3967 | 0.8642 | 0.8619 |
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+ | 0.2774 | 9.0 | 486 | 0.3958 | 0.8616 | 0.8575 |
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+ | 0.2728 | 10.0 | 540 | 0.3959 | 0.8668 | 0.8644 |
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+ | 0.2427 | 11.0 | 594 | 0.3962 | 0.8590 | 0.8550 |
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+ | 0.2425 | 12.0 | 648 | 0.3959 | 0.8642 | 0.8611 |
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+ | 0.2414 | 13.0 | 702 | 0.3959 | 0.8642 | 0.8611 |
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+ | 0.2249 | 14.0 | 756 | 0.3949 | 0.8616 | 0.8582 |
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+ | 0.2391 | 15.0 | 810 | 0.3947 | 0.8616 | 0.8577 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.19.2
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+ - Pytorch 1.11.0+cu113
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+ - Datasets 2.2.1
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+ - Tokenizers 0.12.1