File size: 2,344 Bytes
0a4e7df |
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 66 67 68 69 70 71 72 73 |
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: distilbart-podimo-data-eval-2
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. -->
# distilbart-podimo-data-eval-2
This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5823
- Rouge1: 34.3971
- Rouge2: 7.95
- Rougel: 18.7271
- Rougelsum: 30.9024
- Gen Len: 131.919
## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:--------:|
| 4.1512 | 0.98 | 44 | 3.7806 | 32.727 | 6.5788 | 17.5196 | 29.3777 | 137.2905 |
| 3.6342 | 1.98 | 88 | 3.6421 | 32.709 | 6.7877 | 17.8668 | 29.4636 | 134.6648 |
| 3.3512 | 2.98 | 132 | 3.5819 | 33.5128 | 7.519 | 18.6614 | 30.1142 | 132.2961 |
| 3.141 | 3.98 | 176 | 3.5552 | 33.4795 | 7.3242 | 18.396 | 30.0854 | 132.757 |
| 2.9787 | 4.98 | 220 | 3.5583 | 33.5862 | 7.391 | 18.3568 | 30.2461 | 132.4078 |
| 2.8555 | 5.98 | 264 | 3.5650 | 34.1111 | 7.8008 | 18.7159 | 30.6055 | 131.3603 |
| 2.7648 | 6.98 | 308 | 3.5729 | 34.0981 | 7.6556 | 18.6373 | 30.6269 | 131.2821 |
| 2.6645 | 7.98 | 352 | 3.5823 | 34.3971 | 7.95 | 18.7271 | 30.9024 | 131.919 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.11.0
- Datasets 2.2.1
- Tokenizers 0.12.1
|