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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: mit
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+ base_model: dumitrescustefan/bert-base-romanian-cased-v1
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: teacher_sst2
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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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+ # teacher_sst2
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+
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+ This model is a fine-tuned version of [dumitrescustefan/bert-base-romanian-cased-v1](https://huggingface.co/dumitrescustefan/bert-base-romanian-cased-v1) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5451
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+ - F1: 0.8648
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+ - Roc Auc: 0.8646
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+ - Accuracy: 0.8635
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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: 1e-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: 8
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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+ | 0.3669 | 1.0 | 1053 | 0.4399 | 0.8248 | 0.8238 | 0.8211 |
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+ | 0.2433 | 2.0 | 2106 | 0.4043 | 0.8457 | 0.8458 | 0.8417 |
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+ | 0.1811 | 3.0 | 3159 | 0.4268 | 0.8625 | 0.8622 | 0.8612 |
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+ | 0.1373 | 4.0 | 4212 | 0.4359 | 0.8537 | 0.8545 | 0.8521 |
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+ | 0.1157 | 5.0 | 5265 | 0.4812 | 0.8681 | 0.8684 | 0.8681 |
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+ | 0.0949 | 6.0 | 6318 | 0.5003 | 0.8607 | 0.8604 | 0.8601 |
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+ | 0.0774 | 7.0 | 7371 | 0.5142 | 0.8643 | 0.8641 | 0.8624 |
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+ | 0.0713 | 8.0 | 8424 | 0.5451 | 0.8648 | 0.8646 | 0.8635 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.1
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+ - Pytorch 2.4.0
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.0
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+ "problem_type": "multi_label_classification",
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+ "torch_dtype": "float32",
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