bert-base-uncased-twitter-sentiment-analysis
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5227
- Accuracy: 0.8196
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3228 | 1.0 | 1400 | 0.5574 | 0.8196 |
| 0.3519 | 2.0 | 2800 | 0.5227 | 0.8196 |
Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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Model tree for katsuchi/bert-base-uncased-twitter-sentiment-analysis
Base model
google-bert/bert-base-uncased