---
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: 0.0081
- Precision: 0.9301
- Recall: 0.9323
- F1: 0.9312
- Accuracy: 0.9980

## 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0062        | 1.0   | 6119  | 0.0076          | 0.9353    | 0.9097 | 0.9223 | 0.9978   |
| 0.0284        | 2.0   | 12238 | 0.0073          | 0.9396    | 0.9186 | 0.9290 | 0.9980   |
| 0.0022        | 3.0   | 18357 | 0.0081          | 0.9301    | 0.9323 | 0.9312 | 0.9980   |


### Framework versions

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