File size: 1,649 Bytes
66a2d86 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 |
---
base_model: google/pegasus-xsum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: tidy-tab-model-pegasus-xsum
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# tidy-tab-model-pegasus-xsum
This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9644
- Rouge1: 0.7456
- Rouge2: 0.6153
- Rougel: 0.7401
- Rougelsum: 0.7422
- Gen Len: 5.2607
## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.5893 | 3.7879 | 500 | 1.0234 | 0.7302 | 0.594 | 0.7229 | 0.7244 | 5.3034 |
| 0.9308 | 7.5758 | 1000 | 0.9644 | 0.7456 | 0.6153 | 0.7401 | 0.7422 | 5.2607 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|