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Upload MBartForConditionalGeneration

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  1. README.md +7 -6
  2. config.json +1 -1
  3. model.safetensors +1 -1
README.md CHANGED
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  ---
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- library_name: transformers
 
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  license: mit
 
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  datasets:
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  - skypro1111/ubertext-2-news-verbalized
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- language:
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- - uk
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  widget:
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- - text: "Очікувалось, що цей застосунок буде запущено о 11 ранку 22.08.2025, але розробники затягнули святкування і запуск був відкладений на 2 тижні."
 
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  ---
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  # Model Card for mbart-large-50-verbalization
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  This model is based on the [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) architecture, renowned for its effectiveness in translation and text generation tasks across numerous languages.
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  ## Training Data
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- The model was fine-tuned on a subset of 457,610 sentences from the Ubertext dataset, focusing on news content. The verbalized equivalents were created using Google Gemini Pro, providing a rich basis for learning text transformation tasks.
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  Dataset [skypro1111/ubertext-2-news-verbalized](https://huggingface.co/datasets/skypro1111/ubertext-2-news-verbalized)
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  ## Training Procedure
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- The model underwent 410,000 training steps.
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  ```python
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  from transformers import MBartForConditionalGeneration, AutoTokenizer, Trainer, TrainingArguments
 
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  ---
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+ language:
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+ - uk
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  license: mit
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+ library_name: transformers
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  datasets:
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  - skypro1111/ubertext-2-news-verbalized
 
 
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  widget:
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+ - text: Очікувалось, що цей застосунок буде запущено о 11 ранку 22.08.2025, але розробники
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+ затягнули святкування і запуск був відкладений на 2 тижні.
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  ---
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  # Model Card for mbart-large-50-verbalization
 
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  This model is based on the [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) architecture, renowned for its effectiveness in translation and text generation tasks across numerous languages.
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  ## Training Data
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+ The model was fine-tuned on a subset of 96,780 sentences from the Ubertext dataset, focusing on news content. The verbalized equivalents were created using Google Gemini Pro, providing a rich basis for learning text transformation tasks.
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  Dataset [skypro1111/ubertext-2-news-verbalized](https://huggingface.co/datasets/skypro1111/ubertext-2-news-verbalized)
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  ## Training Procedure
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+ The model underwent 70,000 training steps, which is almost 2 epochs, with further training the results degraded.
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  ```python
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  from transformers import MBartForConditionalGeneration, AutoTokenizer, Trainer, TrainingArguments
config.json CHANGED
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  {
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- "_name_or_path": "./tmp/checkpoint-70000",
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  "_num_labels": 3,
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  "activation_dropout": 0.0,
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  "activation_function": "gelu",
 
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  {
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+ "_name_or_path": "./results/facebook/mbart-large-50-verbalization/checkpoint-410000",
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  "_num_labels": 3,
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  "activation_dropout": 0.0,
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  "activation_function": "gelu",
model.safetensors CHANGED
@@ -1,3 +1,3 @@
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  size 2444578688
 
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  version https://git-lfs.github.com/spec/v1
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