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---
tags:
- generated_from_trainer
datasets:
- uonlp/CulturaX
metrics:
- accuracy
model-index:
- name: gpt2+morf_u0-30-50-x_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: 0.39500633343599556
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+morf_u0-30-50-x_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: 3.3667
- Accuracy: 0.3950
## 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 |
| :-----------: | :---: | :----: | :-------------: | :------: |
| 4.3227 | 0.04 | 10000 | 4.2268 | 0.3161 |
| 4.0305 | 0.07 | 20000 | 3.9455 | 0.3393 |
| 3.8916 | 0.11 | 30000 | 3.8194 | 0.3502 |
| 3.8104 | 0.15 | 40000 | 3.7340 | 0.3580 |
| 3.7491 | 0.19 | 50000 | 3.6770 | 0.3633 |
| 3.7062 | 0.22 | 60000 | 3.6288 | 0.3679 |
| 3.6724 | 0.26 | 70000 | 3.5938 | 0.3714 |
| 3.6399 | 0.3 | 80000 | 3.5652 | 0.3743 |
| 3.6147 | 0.34 | 90000 | 3.5396 | 0.3768 |
| 3.5946 | 0.37 | 100000 | 3.5158 | 0.3791 |
| 3.5726 | 0.41 | 110000 | 3.4986 | 0.3809 |
| 3.5631 | 0.45 | 120000 | 3.4819 | 0.3826 |
| 3.5459 | 0.49 | 130000 | 3.4678 | 0.3842 |
| 3.5304 | 0.52 | 140000 | 3.4535 | 0.3857 |
| 3.5245 | 0.56 | 150000 | 3.4430 | 0.3867 |
| 3.5124 | 0.6 | 160000 | 3.4329 | 0.3877 |
| 3.501 | 0.63 | 170000 | 3.4223 | 0.3890 |
| 3.4934 | 0.67 | 180000 | 3.4130 | 0.3901 |
| 3.4863 | 0.71 | 190000 | 3.4042 | 0.3909 |
| 3.4799 | 0.75 | 200000 | 3.3991 | 0.3914 |
| 3.4682 | 0.78 | 210000 | 3.3909 | 0.3924 |
| 3.4667 | 0.82 | 220000 | 3.3852 | 0.3930 |
| 3.4564 | 0.86 | 230000 | 3.3790 | 0.3936 |
| 3.4581 | 0.9 | 240000 | 3.3753 | 0.3941 |
| 3.4553 | 0.93 | 250000 | 3.3710 | 0.3945 |
| 3.4508 | 0.97 | 260000 | 3.3680 | 0.3949 |
### Framework versions
- Transformers 4.37.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1 |