finetuning-sentiment-model-3000-samples
This model is a fine-tuned version of distilbert-base-uncased on the financial_phrasebank dataset. It achieves the following results on the evaluation set:
- Loss: 0.0731
- Accuracy: 0.9801
- F1: 0.9726
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
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
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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Model tree for halvion/finetuning-sentiment-model-3000-samples
Base model
distilbert/distilbert-base-uncasedDataset used to train halvion/finetuning-sentiment-model-3000-samples
Evaluation results
- Accuracy on financial_phrasebankself-reported0.980
- F1 on financial_phrasebankself-reported0.973