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bart-text-simplification
Notes: the model is still under improvement
This model is a fine-tuned version of facebook/bart-large-cnn on ASSET and TurkCorpus dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.6558
- eval_model_preparation_time: 0.0082
- eval_sari: 59.0183
- eval_runtime: 670.1131
- eval_samples_per_second: 1.343
- eval_steps_per_second: 1.343
- step: 0
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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Tokenizers 0.19.1
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Model tree for Nubletz/bart-text-simplification
Base model
facebook/bart-large-cnn
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Nubletz/bart-text-simplification") model = AutoModelForSeq2SeqLM.from_pretrained("Nubletz/bart-text-simplification", device_map="auto")