metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased-finetuned-sst-2-english
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: trained_dilibert_sentiment_analysis
results: []
trained_dilibert_sentiment_analysis
This model is a fine-tuned version of distilbert/distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3948
- Accuracy: 0.906
- Confusion Matrix: [[174, 46], [48, 732]]
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Confusion Matrix |
|---|---|---|---|---|---|
| No log | 1.0 | 188 | 0.2507 | 0.905 | [[168, 52], [43, 737]] |
| No log | 2.0 | 376 | 0.2797 | 0.904 | [[172, 48], [48, 732]] |
| 0.2241 | 3.0 | 564 | 0.3635 | 0.906 | [[154, 66], [28, 752]] |
| 0.2241 | 4.0 | 752 | 0.3798 | 0.908 | [[171, 49], [43, 737]] |
| 0.2241 | 5.0 | 940 | 0.3948 | 0.906 | [[174, 46], [48, 732]] |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1