metadata
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: denoice-finetuned-xsum
results: []
denoice-finetuned-xsum
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7176
- Rouge1: 72.4979
- Rouge2: 55.09
- Rougel: 72.5668
- Rougelsum: 72.5151
- Gen Len: 16.5209
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: 500
- eval_batch_size: 500
- 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 | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 76 | 0.7237 | 72.7109 | 55.346 | 72.7556 | 72.7163 | 16.4921 |
| No log | 2.0 | 152 | 0.7188 | 72.4823 | 55.1403 | 72.5559 | 72.5034 | 16.5288 |
| No log | 3.0 | 228 | 0.7176 | 72.4979 | 55.09 | 72.5668 | 72.5151 | 16.5209 |
Framework versions
- Transformers 4.36.2
- Pytorch 1.13.1
- Datasets 2.16.1
- Tokenizers 0.15.0