CausalNLP/gpt2-multilingual-20-deu-repair_3epochs
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Model: CausalNLP/gpt2-multilingual-20-deu-repair_3epochs
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---
library_name: transformers
base_model: CausalNLP/gpt2-hf_multilingual-20
tags:
- generated_from_trainer
model-index:
- name: gpt2-multilingual-20-deu-repair_3epochs
results: []
---
<!-- 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-multilingual-20-deu-repair_3epochs
This model is a fine-tuned version of [CausalNLP/gpt2-hf_multilingual-20](https://huggingface.co/CausalNLP/gpt2-hf_multilingual-20) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2187
## 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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 3.2849 | 0.0876 | 500 | 3.3025 |
| 3.2491 | 0.1752 | 1000 | 3.2839 |
| 3.2539 | 0.2628 | 1500 | 3.2729 |
| 3.2063 | 0.3504 | 2000 | 3.2656 |
| 3.2336 | 0.4380 | 2500 | 3.2591 |
| 3.2188 | 0.5256 | 3000 | 3.2539 |
| 3.2212 | 0.6132 | 3500 | 3.2500 |
| 3.2204 | 0.7008 | 4000 | 3.2457 |
| 3.2059 | 0.7884 | 4500 | 3.2427 |
| 3.2236 | 0.8760 | 5000 | 3.2396 |
| 3.2001 | 0.9636 | 5500 | 3.2368 |
| 3.1861 | 1.0512 | 6000 | 3.2354 |
| 3.1757 | 1.1388 | 6500 | 3.2339 |
| 3.1804 | 1.2264 | 7000 | 3.2319 |
| 3.1862 | 1.3140 | 7500 | 3.2297 |
| 3.1533 | 1.4016 | 8000 | 3.2279 |
| 3.1724 | 1.4892 | 8500 | 3.2262 |
| 3.1641 | 1.5768 | 9000 | 3.2249 |
| 3.1587 | 1.6644 | 9500 | 3.2235 |
| 3.1577 | 1.7520 | 10000 | 3.2221 |
| 3.1716 | 1.8396 | 10500 | 3.2212 |
| 3.2024 | 1.9272 | 11000 | 3.2203 |
| 3.1689 | 2.0147 | 11500 | 3.2199 |
| 3.1569 | 2.1023 | 12000 | 3.2198 |
| 3.1717 | 2.1899 | 12500 | 3.2195 |
| 3.1449 | 2.2775 | 13000 | 3.2192 |
| 3.1487 | 2.3651 | 13500 | 3.2190 |
| 3.1555 | 2.4527 | 14000 | 3.2189 |
| 3.1932 | 2.5403 | 14500 | 3.2188 |
| 3.1394 | 2.6279 | 15000 | 3.2187 |
| 3.1678 | 2.7155 | 15500 | 3.2187 |
| 3.1385 | 2.8032 | 16000 | 3.2187 |
| 3.1675 | 2.8908 | 16500 | 3.2187 |
| 3.183 | 2.9784 | 17000 | 3.2187 |
### Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0
- Datasets 4.4.1
- Tokenizers 0.22.1

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"vocab_size": 119547
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