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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: roberta-base
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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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+ model-index:
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+ - name: Finetuned-Roberta-Base-Sentiment-identifier
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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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+ # Finetuned-Roberta-Base-Sentiment-identifier
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+
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+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7332
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+ - F1: 0.6622
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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: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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 | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.8545 | 0.5 | 500 | 0.8251 | 0.6428 |
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+ | 0.7952 | 1.0 | 1000 | 0.7831 | 0.6445 |
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+ | 0.7962 | 1.5 | 1500 | 0.7935 | 0.6495 |
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+ | 0.7669 | 2.01 | 2000 | 0.7544 | 0.6520 |
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+ | 0.7468 | 2.51 | 2500 | 0.7614 | 0.6724 |
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+ | 0.76 | 3.01 | 3000 | 0.7332 | 0.6622 |
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+ | 0.7352 | 3.51 | 3500 | 0.8651 | 0.6036 |
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+ | 0.7454 | 4.01 | 4000 | 0.7420 | 0.6584 |
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+ | 0.7302 | 4.51 | 4500 | 0.7652 | 0.6573 |
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+ | 0.7099 | 5.02 | 5000 | 0.7372 | 0.6697 |
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+ | 0.73 | 5.52 | 5500 | 0.7806 | 0.6654 |
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+ | 0.7265 | 6.02 | 6000 | 0.7476 | 0.6656 |
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+ | 0.7092 | 6.52 | 6500 | 0.7632 | 0.6535 |
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+ | 0.7322 | 7.02 | 7000 | 0.8017 | 0.6126 |
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+ | 0.7168 | 7.52 | 7500 | 0.8046 | 0.6711 |
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+ | 0.7279 | 8.02 | 8000 | 0.7734 | 0.6652 |
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+ | 0.6884 | 8.53 | 8500 | 0.7806 | 0.6662 |
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+ | 0.6942 | 9.03 | 9000 | 0.7790 | 0.6670 |
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+ | 0.6865 | 9.53 | 9500 | 0.7835 | 0.6650 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.1
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.13.3
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