|
--- |
|
base_model: google/pegasus-xsum |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: bart_recommendation_sports_equipment_english |
|
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. --> |
|
|
|
# bart_recommendation_sports_equipment_english |
|
|
|
This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.9511 |
|
- Rouge1: 29.2063 |
|
- Rouge2: 9.5238 |
|
- Rougel: 28.8889 |
|
- Rougelsum: 29.3651 |
|
- Gen Len: 3.4762 |
|
|
|
## 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: 0.0001 |
|
- train_batch_size: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 8 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
|
| No log | 0.96 | 12 | 5.1428 | 25.7937 | 4.7619 | 26.1905 | 26.1905 | 3.3810 | |
|
| No log | 2.0 | 25 | 4.5991 | 28.4127 | 4.7619 | 28.4127 | 28.4127 | 4.2857 | |
|
| No log | 2.96 | 37 | 4.3659 | 30.0000 | 4.7619 | 30.0 | 30.2381 | 3.9048 | |
|
| No log | 4.0 | 50 | 4.2992 | 23.2540 | 4.7619 | 23.1746 | 23.3333 | 3.9524 | |
|
| No log | 4.96 | 62 | 4.1730 | 23.2540 | 4.7619 | 23.1746 | 23.3333 | 3.5714 | |
|
| No log | 6.0 | 75 | 4.0884 | 29.2063 | 14.2857 | 29.2063 | 29.2063 | 3.4762 | |
|
| No log | 6.96 | 87 | 4.0252 | 25.0 | 4.7619 | 24.9206 | 25.2381 | 3.4762 | |
|
| No log | 8.0 | 100 | 4.0019 | 31.5873 | 14.2857 | 31.1905 | 31.4286 | 3.5714 | |
|
| No log | 8.96 | 112 | 3.9648 | 24.2857 | 4.7619 | 24.2857 | 24.7619 | 3.4762 | |
|
| No log | 9.6 | 120 | 3.9511 | 29.2063 | 9.5238 | 28.8889 | 29.3651 | 3.4762 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
