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finetuned_bert_sentiment_classification

Text Classification
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distilbert
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  1. README.md +89 -0
  2. model.safetensors +1 -1
  3. runs/Dec05_04-37-24_4b143aad8e2f/events.out.tfevents.1701751045.4b143aad8e2f.256.4 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: distilbert-base-uncased
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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: finetuned_bert_sentiment_classification
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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_bert_sentiment_classification
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.9785
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+ - Accuracy: 0.78
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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: 30
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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 | 1.0 | 68 | 0.6297 | 0.73 |
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+ | No log | 2.0 | 136 | 0.9044 | 0.73 |
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+ | No log | 3.0 | 204 | 1.2008 | 0.78 |
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+ | No log | 4.0 | 272 | 1.4143 | 0.75 |
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+ | No log | 5.0 | 340 | 1.4934 | 0.76 |
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+ | No log | 6.0 | 408 | 1.5581 | 0.765 |
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+ | No log | 7.0 | 476 | 1.6158 | 0.78 |
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+ | 0.1371 | 8.0 | 544 | 1.6786 | 0.785 |
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+ | 0.1371 | 9.0 | 612 | 1.7112 | 0.78 |
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+ | 0.1371 | 10.0 | 680 | 1.7416 | 0.78 |
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+ | 0.1371 | 11.0 | 748 | 1.7667 | 0.78 |
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+ | 0.1371 | 12.0 | 816 | 1.7937 | 0.78 |
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+ | 0.1371 | 13.0 | 884 | 1.8139 | 0.78 |
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+ | 0.1371 | 14.0 | 952 | 1.8347 | 0.78 |
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+ | 0.0002 | 15.0 | 1020 | 1.8531 | 0.785 |
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+ | 0.0002 | 16.0 | 1088 | 1.8645 | 0.78 |
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+ | 0.0002 | 17.0 | 1156 | 1.8798 | 0.78 |
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+ | 0.0002 | 18.0 | 1224 | 1.8964 | 0.78 |
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+ | 0.0002 | 19.0 | 1292 | 1.9097 | 0.78 |
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+ | 0.0002 | 20.0 | 1360 | 1.9206 | 0.78 |
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+ | 0.0002 | 21.0 | 1428 | 1.9310 | 0.78 |
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+ | 0.0002 | 22.0 | 1496 | 1.9410 | 0.78 |
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+ | 0.0001 | 23.0 | 1564 | 1.9494 | 0.78 |
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+ | 0.0001 | 24.0 | 1632 | 1.9566 | 0.78 |
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+ | 0.0001 | 25.0 | 1700 | 1.9628 | 0.78 |
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+ | 0.0001 | 26.0 | 1768 | 1.9681 | 0.78 |
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+ | 0.0001 | 27.0 | 1836 | 1.9730 | 0.78 |
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+ | 0.0001 | 28.0 | 1904 | 1.9761 | 0.78 |
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+ | 0.0001 | 29.0 | 1972 | 1.9779 | 0.78 |
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+ | 0.0 | 30.0 | 2040 | 1.9785 | 0.78 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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