out / README.md
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Data-Lab/ruRoberta-large_classification_v0.1
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---
base_model: ai-forever/ruRoberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: out
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. -->
# out
This model is a fine-tuned version of [ai-forever/ruRoberta-large](https://huggingface.co/ai-forever/ruRoberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5844
- Accuracy: 0.7432
- Precision: 0.5523
- Recall: 0.7432
- F1: 0.6337
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 0
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3721 | 1.82 | 500 | 0.5791 | 0.7432 | 0.5523 | 0.7432 | 0.6337 |
| 0.6021 | 3.64 | 1000 | 0.5844 | 0.7432 | 0.5523 | 0.7432 | 0.6337 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3