---
tags:
- generated_from_trainer
datasets:
- uonlp/CulturaX
metrics:
- accuracy
model-index:
- name: gpt2_cx-en_00000-00009_50k
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: uonlp/CulturaX en
      type: uonlp/CulturaX
      args: en
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.36165373273858764
license: mit
language:
- en
---

<!-- 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. -->

# gpt2_cx-en_00000-00009_50k

This model is a fine-tuned version of [](https://huggingface.co/) on the uonlp/CulturaX en dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5834
- Accuracy: 0.3617

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 4.586         | 0.04  | 10000  | 4.4977          | 0.2821   |
| 4.2706        | 0.08  | 20000  | 4.1928          | 0.3058   |
| 4.1189        | 0.12  | 30000  | 4.0469          | 0.3179   |
| 4.0314        | 0.16  | 40000  | 3.9610          | 0.3253   |
| 3.9704        | 0.2   | 50000  | 3.8977          | 0.3311   |
| 3.923         | 0.24  | 60000  | 3.8486          | 0.3353   |
| 3.888         | 0.28  | 70000  | 3.8084          | 0.3390   |
| 3.8529        | 0.32  | 80000  | 3.7777          | 0.3423   |
| 3.832         | 0.36  | 90000  | 3.7526          | 0.3446   |
| 3.8102        | 0.4   | 100000 | 3.7277          | 0.3470   |
| 3.7876        | 0.44  | 110000 | 3.7073          | 0.3490   |
| 3.7686        | 0.48  | 120000 | 3.6922          | 0.3506   |
| 3.7585        | 0.52  | 130000 | 3.6750          | 0.3522   |
| 3.7459        | 0.56  | 140000 | 3.6620          | 0.3535   |
| 3.7378        | 0.6   | 150000 | 3.6501          | 0.3545   |
| 3.7181        | 0.64  | 160000 | 3.6385          | 0.3559   |
| 3.7139        | 0.68  | 170000 | 3.6293          | 0.3568   |
| 3.6958        | 0.72  | 180000 | 3.6201          | 0.3578   |
| 3.6872        | 0.76  | 190000 | 3.6122          | 0.3585   |
| 3.6888        | 0.8   | 200000 | 3.6060          | 0.3592   |
| 3.6765        | 0.84  | 210000 | 3.6001          | 0.3599   |
| 3.6734        | 0.88  | 220000 | 3.5945          | 0.3604   |
| 3.6669        | 0.92  | 230000 | 3.5891          | 0.3611   |
| 3.6696        | 0.96  | 240000 | 3.5856          | 0.3614   |


### Framework versions

- Transformers 4.37.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1