t5-small-finetuned-cnndm2-wikihow1
This model is a fine-tuned version of Chikashi/t5-small-finetuned-cnndm1-wikihow1 on the cnn_dailymail dataset. It achieves the following results on the evaluation set:
- Loss: 1.6305
- Rouge1: 24.6317
- Rouge2: 11.8655
- Rougel: 20.3598
- Rougelsum: 23.2467
- Gen Len: 18.9996
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: 0.0003
- 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: 1
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
1.8062 | 1.0 | 71779 | 1.6305 | 24.6317 | 11.8655 | 20.3598 | 23.2467 | 18.9996 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1
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