---
library_name: transformers
license: apache-2.0
base_model: deepvk/deberta-v1-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: deepvk_deberta-v1-base__bs32_max_len128_ep10_lr5e-05_lr_sheduler_linear
  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. -->

# deepvk_deberta-v1-base__bs32_max_len128_ep10_lr5e-05_lr_sheduler_linear

This model is a fine-tuned version of [deepvk/deberta-v1-base](https://huggingface.co/deepvk/deberta-v1-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1221
- Model Preparation Time: 0.003
- Accuracy: 0.9631
- F1: 0.5409
- Precision: 0.5667
- Recall: 0.5172

## 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: 32
- eval_batch_size: 32
- seed: 28
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:|:------:|:---------:|:------:|
| 0.0992        | 1.0   | 1357 | 0.0963          | 0.003                  | 0.9669   | 0.4686 | 0.7171    | 0.3480 |
| 0.0886        | 2.0   | 2714 | 0.0884          | 0.003                  | 0.9679   | 0.5236 | 0.6958    | 0.4197 |
| 0.0817        | 3.0   | 4071 | 0.0888          | 0.003                  | 0.9678   | 0.5447 | 0.6710    | 0.4585 |
| 0.0725        | 4.0   | 5428 | 0.0927          | 0.003                  | 0.9657   | 0.5345 | 0.6219    | 0.4687 |
| 0.0619        | 5.0   | 6785 | 0.0978          | 0.003                  | 0.9650   | 0.5390 | 0.6026    | 0.4876 |
| 0.0502        | 6.0   | 8142 | 0.1075          | 0.003                  | 0.9643   | 0.5391 | 0.5886    | 0.4973 |
| 0.0407        | 7.0   | 9499 | 0.1221          | 0.003                  | 0.9631   | 0.5409 | 0.5667    | 0.5172 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0