metadata
license: apache-2.0
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
base_model: sshleifer/distilbart-cnn-12-6
model-index:
- name: etsummerizer_v2
results: []
etsummerizer_v2
This model is a fine-tuned version of sshleifer/distilbart-cnn-12-6 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3484
- Rouge1: 0.5448
- Rouge2: 0.3092
- Rougel: 0.4363
- Rougelsum: 0.4370
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 3.5 | 1.0 | 30 | 0.5565 | 0.5111 | 0.2863 | 0.4092 | 0.4093 |
| 0.3056 | 2.0 | 60 | 0.3612 | 0.5267 | 0.3021 | 0.4277 | 0.4286 |
| 0.1716 | 3.0 | 90 | 0.3484 | 0.5448 | 0.3092 | 0.4363 | 0.4370 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0+cpu
- Datasets 2.1.0
- Tokenizers 0.13.3