Abror Shopulatov
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update model card README.md
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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: uzroberta-sentiment-analysis
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# uzroberta-sentiment-analysis
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This model is a fine-tuned version of [rifkat/uztext-3Gb-BPE-Roberta](https://huggingface.co/rifkat/uztext-3Gb-BPE-Roberta) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5718
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- Precision: 0.9113
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- Recall: 0.8869
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- F1: 0.8989
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- Accuracy: 0.896
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 4
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.1595 | 1.0 | 1125 | 0.4438 | 0.8971 | 0.8523 | 0.8741 | 0.872 |
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| 0.1891 | 2.0 | 2250 | 0.4157 | 0.8961 | 0.9012 | 0.8987 | 0.894 |
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| 0.1201 | 3.0 | 3375 | 0.5024 | 0.9074 | 0.8830 | 0.8950 | 0.892 |
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| 0.0772 | 4.0 | 4500 | 0.5718 | 0.9113 | 0.8869 | 0.8989 | 0.896 |
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### Framework versions
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- Transformers 4.20.1
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- Pytorch 1.12.0+cu116
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- Datasets 2.3.2
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- Tokenizers 0.12.1
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