uzbek-sentiment-analysis
It achieves the following results on the evaluation set:
- eval_loss: 0.6374
- eval_accuracy: {'accuracy': 0.7862348178137651}
- eval_f1score: {'f1': 0.7880364308572618}
- eval_runtime: 7.593
- eval_samples_per_second: 162.65
- eval_steps_per_second: 20.414
- step: 0
Model description
uzbek-sentiment-analysis modelidan foydalanish.
from transformers import pipeline
pipe = pipeline('sentimennt-analysis', model='ai-nightcoder/uzbek-sentiment-analysis-v5')
text = "bu ovqatni men juda ham yaxshi ko'raman."
pipe(text)[0]['label']
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: 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_steps: 864
- num_epochs: 7
Framework versions
- Transformers 4.40.1
- Pytorch 2.4.0.dev20240416+cu121
- Datasets 1.18.3
- Tokenizers 0.19.1
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