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--- |
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license: apache-2.0 |
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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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base_model: distilbert-base-uncased |
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model-index: |
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- name: distilbert-base-uncased-sentiment-reddit-crypto |
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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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# distilbert-base-uncased-sentiment-reddit-crypto |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the crypto-related reddit comments dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3070 |
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- Accuracy: 0.8915 |
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Accuracy on the final test set was: 0.8641 |
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## Training and evaluation data |
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Training and validation data collected from 2 sources: |
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1. [Kaggle reddit cryptocurrency posts and comments](https://www.kaggle.com/datasets/gpreda/reddit-cryptocurrency) |
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2. [Kaggle reddit cryptocurrency related posts from various subreddits](https://www.kaggle.com/datasets/leukipp/reddit-crypto-data). Comments from subreddits: `'cryptocurrency', 'bitcoin', 'ethereum', 'dogecoin'` were extracted. |
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Final test data source is from https://www.surgehq.ai/datasets/crypto-sentiment-dataset. |
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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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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 0.2823 | 1.0 | 5109 | 0.2658 | 0.8840 | |
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| 0.1905 | 2.0 | 10218 | 0.3070 | 0.8915 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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