|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: distilbert-base-uncased-sentiment-reddit-crypto |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# distilbert-base-uncased-sentiment-reddit-crypto |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the crypto-related reddit comments dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3070 |
|
- Accuracy: 0.8915 |
|
|
|
Accuracy on the final test set was: 0.8641 |
|
|
|
## Training and evaluation data |
|
|
|
Training and validation data collected from 2 sources: |
|
|
|
1. [Kaggle reddit cryptocurrency posts and comments](https://www.kaggle.com/datasets/gpreda/reddit-cryptocurrency) |
|
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. |
|
|
|
Final test data source is from https://www.surgehq.ai/datasets/crypto-sentiment-dataset. |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 2e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 2 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 0.2823 | 1.0 | 5109 | 0.2658 | 0.8840 | |
|
| 0.1905 | 2.0 | 10218 | 0.3070 | 0.8915 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.25.1 |
|
- Pytorch 1.13.1+cu116 |
|
- Datasets 2.8.0 |
|
- Tokenizers 0.13.2 |
|
|
