t5-small-finetuned-cnndm3-wikihow2
This model is a fine-tuned version of Chikashi/t5-small-finetuned-cnndm2-wikihow2 on the cnn_dailymail dataset. It achieves the following results on the evaluation set:
- Loss: 1.6265
- Rouge1: 24.6704
- Rouge2: 11.9038
- Rougel: 20.3622
- Rougelsum: 23.2612
- Gen Len: 18.9997
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 |
---|---|---|---|---|---|---|---|---|
1.8071 | 1.0 | 71779 | 1.6265 | 24.6704 | 11.9038 | 20.3622 | 23.2612 | 18.9997 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1
- Downloads last month
- 2
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.