---
license: apache-2.0
tags:
- generated_from_trainer
base_model: distilbert-base-uncased
model-index:
- name: uzb-senAnalys
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# 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