metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Sentiment_Analysis_in_Social_Media_SonatafyAI_BERT_v1
results: []
Sentiment_Analysis_in_Social_Media_SonatafyAI_BERT_v1
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0893
- Accuracy: 0.8495
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5082 | 1.0 | 687 | 0.4134 | 0.8481 |
| 0.3337 | 2.0 | 1374 | 0.4205 | 0.8499 |
| 0.1865 | 3.0 | 2061 | 0.5330 | 0.8477 |
| 0.1099 | 4.0 | 2748 | 0.8024 | 0.8299 |
| 0.1007 | 5.0 | 3435 | 0.7997 | 0.8455 |
| 0.0393 | 6.0 | 4122 | 0.8675 | 0.8419 |
| 0.0368 | 7.0 | 4809 | 0.9558 | 0.8455 |
| 0.0308 | 8.0 | 5496 | 1.0125 | 0.8401 |
| 0.0157 | 9.0 | 6183 | 1.0818 | 0.8423 |
| 0.0156 | 10.0 | 6870 | 1.0893 | 0.8495 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1