transformers safetensors bert text-classification generated_from_trainer dataset:polemo2-official base_model:allegro/herbert-base-cased base_model:finetune:allegro/herbert-base-cased license:cc-by-4.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: allegro/herbert-base-cased
datasets:
- polemo2-official
library_name: transformers
license: cc-by-4.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: sentiment_class6
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: polemo2-official
      type: polemo2-official
      config: all_text
      split: test
      args: all_text
    metrics:
    - type: accuracy
      value: 0.8951219512195122
      name: Accuracy
---

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# results

This model is a fine-tuned version of [allegro/herbert-base-cased](https://huggingface.co/allegro/herbert-base-cased) on the polemo2-official dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3520
- Accuracy: 0.8951

## 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: 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3688        | 1.0   | 411  | 0.2971          | 0.8805   |
| 0.2472        | 2.0   | 822  | 0.2747          | 0.9061   |
| 0.1286        | 3.0   | 1233 | 0.3520          | 0.8951   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
