---
tags:
- generated_from_trainer
model-index:
- name: sentiment-polish-gpt2-large
  results: []
license: mit
datasets:
- clarin-pl/polemo2-official
language:
- pl
metrics:
- accuracy
---

<!-- 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. -->

# sentiment-polish-gpt2-large

This model is a fine-tuned version of [sdadas/polish-gpt2-large](https://huggingface.co/sdadas/polish-gpt2-large) on the [polemo2-official](https://huggingface.co/datasets/clarin-pl/polemo2-official) dataset.
It achieves the following results on the evaluation set:
- epoch: 10.0
- eval_accuracy: 0.9634
- eval_loss: 0.3139
- eval_runtime: 132.9089
- eval_samples_per_second: 197.428
- eval_steps_per_second: 98.714
- step: 65610

## Model description

Trained from [polish-gpt2-large](https://huggingface.co/sdadas/polish-gpt2-large)

## Intended uses & limitations

Sentiment analysis - neutral/negative/positive/ambiguous

## Training and evaluation data

Merged all rows from [polemo2-official](https://huggingface.co/datasets/clarin-pl/polemo2-official) dataset.

Discarded rows with length > 512.

Train/test split: 80%/20%

Datacollator:
```py
data_collator = DataCollatorWithPadding(
  tokenizer=tokenizer,
  padding="longest",
  max_length=MAX_INPUT_LENGTH,
  pad_to_multiple_of=8
)
```

## Training procedure

GPU: 2x RTX 4060Ti 16GB

Training time: 29:16:50

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1