---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mdeberta-v3-base-subjectivity-sentiment-bulgarian
  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. -->

# mdeberta-v3-base-subjectivity-sentiment-bulgarian

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4555
- Macro F1: 0.8291
- Macro P: 0.8289
- Macro R: 0.8293
- Subj F1: 0.8100
- Subj P: 0.8071
- Subj R: 0.8129
- Accuracy: 0.8312

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Macro P | Macro R | Subj F1 | Subj P | Subj R | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------:|:-------:|:-------:|:------:|:------:|:--------:|
| No log        | 1.0   | 46   | 0.6893          | 0.4013   | 0.6563  | 0.5378  | 0.6282  | 0.4626 | 0.9784 | 0.4873   |
| No log        | 2.0   | 92   | 0.5960          | 0.7650   | 0.7791  | 0.7616  | 0.7194  | 0.7982 | 0.6547 | 0.7739   |
| No log        | 3.0   | 138  | 0.5138          | 0.7928   | 0.7939  | 0.7920  | 0.7664  | 0.7778 | 0.7554 | 0.7962   |
| No log        | 4.0   | 184  | 0.4831          | 0.8054   | 0.8073  | 0.8042  | 0.7794  | 0.7970 | 0.7626 | 0.8089   |
| No log        | 5.0   | 230  | 0.4792          | 0.8082   | 0.8115  | 0.8063  | 0.7807  | 0.8077 | 0.7554 | 0.8121   |
| No log        | 6.0   | 276  | 0.4555          | 0.8291   | 0.8289  | 0.8293  | 0.8100  | 0.8071 | 0.8129 | 0.8312   |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0