metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased-finetuned-sst-2-english
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: twitter_financial_sentiment
results: []
twitter_financial_sentiment
This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3798
- Precision: 0.8651
- Recall: 0.8643
- F1: 0.8645
- Accuracy: 0.8643
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.5218 | 1.0 | 597 | 0.4166 | 0.8382 | 0.8354 | 0.8365 | 0.8354 |
| 0.2876 | 2.0 | 1194 | 0.3783 | 0.8607 | 0.8597 | 0.8592 | 0.8597 |
| 0.2956 | 3.0 | 1791 | 0.3798 | 0.8651 | 0.8643 | 0.8645 | 0.8643 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.21.0