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---
library_name: transformers
license: cc-by-4.0
base_model: allegro/herbert-base-cased
tags:
- generated_from_trainer
datasets:
- polemo2-official
metrics:
- accuracy
model-index:
- name: sentiment_class6
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: polemo2-official
type: polemo2-official
config: all_text
split: test
args: all_text
metrics:
- name: Accuracy
type: accuracy
value: 0.8951219512195122
---
<!-- 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. -->
# 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
|