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End of training

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README.md ADDED
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+ ---
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+ base_model: cardiffnlp/bert-base-multilingual-cased-sentiment-multilingual
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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: Improved-mBERT-attempt2
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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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+ # Improved-mBERT-attempt2
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+
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+ This model is a fine-tuned version of [cardiffnlp/bert-base-multilingual-cased-sentiment-multilingual](https://huggingface.co/cardiffnlp/bert-base-multilingual-cased-sentiment-multilingual) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4767
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+ - Accuracy: 0.83
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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: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 10
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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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+ | No log | 0.07 | 50 | 0.4113 | 0.83 |
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+ | No log | 0.14 | 100 | 0.4244 | 0.8 |
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+ | No log | 0.21 | 150 | 0.5003 | 0.79 |
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+ | No log | 0.27 | 200 | 0.6269 | 0.72 |
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+ | No log | 0.34 | 250 | 0.4152 | 0.79 |
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+ | No log | 0.41 | 300 | 0.5146 | 0.78 |
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+ | No log | 0.48 | 350 | 0.4050 | 0.83 |
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+ | No log | 0.55 | 400 | 0.3897 | 0.83 |
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+ | No log | 0.62 | 450 | 0.3976 | 0.82 |
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+ | 0.4388 | 0.68 | 500 | 0.5089 | 0.78 |
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+ | 0.4388 | 0.75 | 550 | 0.4276 | 0.82 |
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+ | 0.4388 | 0.82 | 600 | 0.4009 | 0.83 |
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+ | 0.4388 | 0.89 | 650 | 0.5864 | 0.73 |
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+ | 0.4388 | 0.96 | 700 | 0.4581 | 0.79 |
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+ | 0.4388 | 1.03 | 750 | 0.4783 | 0.8 |
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+ | 0.4388 | 1.1 | 800 | 0.3497 | 0.88 |
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+ | 0.4388 | 1.16 | 850 | 0.5715 | 0.75 |
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+ | 0.4388 | 1.23 | 900 | 0.3953 | 0.84 |
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+ | 0.4388 | 1.3 | 950 | 0.4425 | 0.85 |
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+ | 0.3525 | 1.37 | 1000 | 0.4271 | 0.86 |
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+ | 0.3525 | 1.44 | 1050 | 0.4252 | 0.84 |
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+ | 0.3525 | 1.51 | 1100 | 0.4297 | 0.85 |
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+ | 0.3525 | 1.58 | 1150 | 0.5833 | 0.8 |
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+ | 0.3525 | 1.64 | 1200 | 0.5043 | 0.81 |
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+ | 0.3525 | 1.71 | 1250 | 0.3593 | 0.87 |
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+ | 0.3525 | 1.78 | 1300 | 0.3999 | 0.8 |
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+ | 0.3525 | 1.85 | 1350 | 0.4493 | 0.8 |
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+ | 0.3525 | 1.92 | 1400 | 0.4266 | 0.82 |
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+ | 0.3525 | 1.99 | 1450 | 0.5052 | 0.81 |
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+ | 0.304 | 2.05 | 1500 | 0.4767 | 0.83 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.1
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.7
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+ - Tokenizers 0.14.1
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