distilbert-sentiment-analysis
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1302
- Accuracy: {'accuracy': 0.9528820856254484}
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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.2055 | 1.0 | 610 | 0.1353 | {'accuracy': 0.9492944271705334} |
0.1416 | 2.0 | 1220 | 0.1264 | {'accuracy': 0.9521645539344654} |
0.1115 | 3.0 | 1830 | 0.1302 | {'accuracy': 0.9528820856254484} |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
- Downloads last month
- 2
Model tree for harshilj0310/distilbert-sentiment-analysis
Base model
distilbert/distilbert-base-uncased
Adapter
this model