tst-summarization
This model is a fine-tuned version of t5-small on the searde/dataset-financial-documents-2 3.0.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0730
- Rouge1: 90.0297
- Rouge2: 68.9083
- Rougel: 89.8451
- Rougelsum: 89.9838
- Gen Len: 38.9598
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1
- Datasets 2.13.1
- Tokenizers 0.13.3
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Dataset used to train searde/model-financial-documents
Evaluation results
- Rouge1 on searde/dataset-financial-documents-2 3.0.0validation set self-reported90.030