---
library_name: transformers
license: cc-by-4.0
base_model: NbAiLab/nb-bert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: nbbert_indirect_speech
  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. -->

# nbbert_indirect_speech

This model is a fine-tuned version of [NbAiLab/nb-bert-base](https://huggingface.co/NbAiLab/nb-bert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.8555
- Precision: 0.8632
- Recall: 0.8555
- F1: 0.8537
- Loss: 0.6652

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Accuracy | Precision | Recall | F1     | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------:|:------:|:------:|:---------------:|
| No log        | 1.0   | 13   | 0.5937   | 0.6744    | 0.5937 | 0.4918 | 0.7937          |
| No log        | 2.0   | 26   | 0.7974   | 0.8004    | 0.7974 | 0.7938 | 0.5315          |
| No log        | 3.0   | 39   | 0.7321   | 0.7927    | 0.7321 | 0.7257 | 0.7020          |
| No log        | 4.0   | 52   | 0.7905   | 0.7812    | 0.7905 | 0.7856 | 0.5378          |
| No log        | 5.0   | 65   | 0.8130   | 0.8173    | 0.8130 | 0.8093 | 0.5648          |
| No log        | 6.0   | 78   | 0.7978   | 0.7880    | 0.7978 | 0.7927 | 0.5450          |
| No log        | 7.0   | 91   | 0.8313   | 0.8468    | 0.8313 | 0.8274 | 0.5858          |
| No log        | 8.0   | 104  | 0.8313   | 0.8373    | 0.8313 | 0.8272 | 0.5247          |
| No log        | 9.0   | 117  | 0.8294   | 0.8499    | 0.8294 | 0.8293 | 0.6528          |
| No log        | 10.0  | 130  | 0.8414   | 0.8558    | 0.8414 | 0.8385 | 0.5475          |
| No log        | 11.0  | 143  | 0.8472   | 0.8611    | 0.8472 | 0.8472 | 0.5893          |
| No log        | 12.0  | 156  | 0.8421   | 0.8518    | 0.8421 | 0.8436 | 0.6162          |
| No log        | 13.0  | 169  | 0.8382   | 0.8370    | 0.8382 | 0.8370 | 0.5678          |
| No log        | 14.0  | 182  | 0.8502   | 0.8531    | 0.8502 | 0.8479 | 0.5941          |
| No log        | 15.0  | 195  | 0.8521   | 0.8666    | 0.8521 | 0.8500 | 0.7085          |
| No log        | 16.0  | 208  | 0.8511   | 0.8571    | 0.8511 | 0.8502 | 0.6244          |
| No log        | 17.0  | 221  | 0.8548   | 0.8641    | 0.8548 | 0.8526 | 0.6625          |
| No log        | 18.0  | 234  | 0.8553   | 0.8646    | 0.8553 | 0.8529 | 0.6697          |
| No log        | 18.48 | 240  | 0.8555   | 0.8632    | 0.8555 | 0.8537 | 0.6652          |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Tokenizers 0.21.0