---
library_name: transformers
base_model: DeepPavlov/rubert-base-cased-conversational
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert_ner_output
  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. -->

# bert_ner_output

This model is a fine-tuned version of [DeepPavlov/rubert-base-cased-conversational](https://huggingface.co/DeepPavlov/rubert-base-cased-conversational) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0114
- Precision: 0.9004
- Recall: 0.9049
- F1: 0.9026
- Accuracy: 0.9972

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- 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
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0038        | 1.0   | 6119  | 0.0109          | 0.8962    | 0.9070 | 0.9016 | 0.9972   |
| 0.0193        | 2.0   | 12238 | 0.0114          | 0.9004    | 0.9049 | 0.9026 | 0.9972   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3