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fine-tune-Pegasus
This model is a fine-tuned version of google/pegasus-large on the xsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.3242
- Rouge1: 17.993
- Rouge2: 2.9392
- Rougel: 12.313
- Rougelsum: 13.3091
- Gen Len: 67.0552
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: 6.35e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 1.0
- mixed_precision_training: Native AMP
Training results
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.1
- Datasets 1.17.0
- Tokenizers 0.10.3
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Dataset used to train QuickRead/fine-tune-Pegasus
Evaluation results
- Rouge1 on xsumself-reported17.993
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("QuickRead/fine-tune-Pegasus") model = AutoModelForSeq2SeqLM.from_pretrained("QuickRead/fine-tune-Pegasus")