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---
tags:
- generated_from_trainer
datasets:
- uonlp/CulturaX
metrics:
- accuracy
model-index:
- name: gpt2_cx-cs_00000-00019_50k
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: uonlp/CulturaX cs
type: uonlp/CulturaX
args: cs
metrics:
- name: Accuracy
type: accuracy
value: 0.38830943632679016
license: mit
language:
- cs
---
<!-- 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-cs_00000-00019_50k
This model is a fine-tuned version of [](https://huggingface.co/) on the uonlp/CulturaX cs dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5060
- Accuracy: 0.3883
## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 4.729 | 0.04 | 10000 | 4.6077 | 0.2836 |
| 4.3383 | 0.07 | 20000 | 4.2318 | 0.3162 |
| 4.1706 | 0.11 | 30000 | 4.0651 | 0.3316 |
| 4.0594 | 0.15 | 40000 | 3.9599 | 0.3416 |
| 3.9842 | 0.19 | 50000 | 3.8825 | 0.3487 |
| 3.9298 | 0.22 | 60000 | 3.8244 | 0.3545 |
| 3.8777 | 0.26 | 70000 | 3.7791 | 0.3592 |
| 3.8455 | 0.3 | 80000 | 3.7436 | 0.3629 |
| 3.8104 | 0.33 | 90000 | 3.7120 | 0.3660 |
| 3.7908 | 0.37 | 100000 | 3.6862 | 0.3687 |
| 3.7613 | 0.41 | 110000 | 3.6628 | 0.3712 |
| 3.7492 | 0.45 | 120000 | 3.6434 | 0.3731 |
| 3.7228 | 0.48 | 130000 | 3.6246 | 0.3751 |
| 3.7127 | 0.52 | 140000 | 3.6090 | 0.3767 |
| 3.694 | 0.56 | 150000 | 3.5962 | 0.3783 |
| 3.6871 | 0.59 | 160000 | 3.5831 | 0.3797 |
| 3.6784 | 0.63 | 170000 | 3.5708 | 0.3810 |
| 3.6606 | 0.67 | 180000 | 3.5593 | 0.3823 |
| 3.646 | 0.71 | 190000 | 3.5491 | 0.3835 |
| 3.6453 | 0.74 | 200000 | 3.5410 | 0.3843 |
| 3.6393 | 0.78 | 210000 | 3.5342 | 0.3851 |
| 3.6207 | 0.82 | 220000 | 3.5280 | 0.3857 |
| 3.6288 | 0.86 | 230000 | 3.5218 | 0.3865 |
| 3.6176 | 0.89 | 240000 | 3.5151 | 0.3872 |
| 3.6099 | 0.93 | 250000 | 3.5108 | 0.3878 |
| 3.6093 | 0.97 | 260000 | 3.5079 | 0.3881 |
### Framework versions
- Transformers 4.37.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1 |