CausalNLP/gpt2-multilingual-20-arabic-repair_3epochs_lr1e-4_bf16
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Model: CausalNLP/gpt2-multilingual-20-arabic-repair_3epochs_lr1e-4_bf16
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---
library_name: transformers
base_model: CausalNLP/gpt2-hf_multilingual-20
tags:
- generated_from_trainer
model-index:
- name: gpt2-multilingual-20-arabic-repair_3epochs_lr1e-4_bf16
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-arabic-repair_3epochs_lr1e-4_bf16
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: 3.2206
## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use 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_ratio: 0.1
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 3.295 | 0.0799 | 500 | 3.3488 |
| 3.2752 | 0.1597 | 1000 | 3.3363 |
| 3.2844 | 0.2396 | 1500 | 3.3416 |
| 3.3059 | 0.3194 | 2000 | 3.3491 |
| 3.335 | 0.3993 | 2500 | 3.3387 |
| 3.2845 | 0.4791 | 3000 | 3.3301 |
| 3.2458 | 0.5590 | 3500 | 3.3216 |
| 3.2689 | 0.6388 | 4000 | 3.3129 |
| 3.2737 | 0.7187 | 4500 | 3.3069 |
| 3.2604 | 0.7985 | 5000 | 3.3000 |
| 3.2255 | 0.8784 | 5500 | 3.2936 |
| 3.239 | 0.9582 | 6000 | 3.2882 |
| 3.2594 | 1.0380 | 6500 | 3.2832 |
| 3.2123 | 1.1179 | 7000 | 3.2780 |
| 3.2347 | 1.1977 | 7500 | 3.2726 |
| 3.2197 | 1.2776 | 8000 | 3.2671 |
| 3.2028 | 1.3574 | 8500 | 3.2615 |
| 3.195 | 1.4373 | 9000 | 3.2557 |
| 3.2049 | 1.5171 | 9500 | 3.2510 |
| 3.1649 | 1.5970 | 10000 | 3.2458 |
| 3.1984 | 1.6768 | 10500 | 3.2409 |
| 3.2787 | 1.7567 | 11000 | 3.2374 |
| 3.1966 | 1.8365 | 11500 | 3.2334 |
| 3.166 | 1.9164 | 12000 | 3.2305 |
| 3.2029 | 1.9962 | 12500 | 3.2272 |
| 3.1629 | 2.0760 | 13000 | 3.2268 |
| 3.1115 | 2.1559 | 13500 | 3.2253 |
| 3.184 | 2.2357 | 14000 | 3.2239 |
| 3.1391 | 2.3156 | 14500 | 3.2229 |
| 3.1341 | 2.3954 | 15000 | 3.2220 |
| 3.1623 | 2.4753 | 15500 | 3.2214 |
| 3.1565 | 2.5551 | 16000 | 3.2211 |
| 3.1129 | 2.6350 | 16500 | 3.2208 |
| 3.2043 | 2.7148 | 17000 | 3.2207 |
| 3.1044 | 2.7947 | 17500 | 3.2206 |
| 3.1922 | 2.8746 | 18000 | 3.2206 |
| 3.1229 | 2.9544 | 18500 | 3.2206 |
### Framework versions
- Transformers 4.57.4
- Pytorch 2.9.1+cu128
- Datasets 4.4.2
- Tokenizers 0.22.2

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"vocab_size": 119547
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