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---
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license: apache-2.0
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base_model: distilbert/distilbert-base-uncased-finetuned-sst-2-english
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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: finetuning-sentiment-analysis-model-team-28
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results: []
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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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# finetuning-sentiment-analysis-model-team-28
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7661
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- Accuracy: 0.6771
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- F1: 0.7964
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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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- lr_scheduler_warmup_steps: 500
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 0.5319 | 1.0 | 175 | 0.4260 | 0.7929 | 0.8812 |
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| 0.4606 | 2.0 | 350 | 0.6068 | 0.7514 | 0.8545 |
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| 0.3351 | 3.0 | 525 | 0.7661 | 0.6771 | 0.7964 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.20.0
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- Tokenizers 0.15.2
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