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t5-base-billsum_model
This model is a fine-tuned version of t5-base on the billsum dataset. It achieves the following results on the evaluation set:
- eval_loss: 1.3212
- eval_rouge1: 0.2449
- eval_rouge2: 0.199
- eval_rougeL: 0.2377
- eval_rougeLsum: 0.2377
- eval_gen_len: 18.9997
- eval_bleu: 0.0019
- eval_runtime: 199.0696
- eval_samples_per_second: 16.421
- eval_steps_per_second: 1.03
- epoch: 9.0
- step: 2666
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3