|
--- |
|
tags: |
|
- summarization |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: bart-large-cnn-samsum-rescom-finetuned-resume-summarizer-10-epoch |
|
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-large-cnn-samsum-rescom-finetuned-resume-summarizer-10-epoch |
|
|
|
This model is a fine-tuned version of [Ameer05/model-token-repo](https://huggingface.co/Ameer05/model-token-repo) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.5216 |
|
- Rouge1: 59.5791 |
|
- Rouge2: 51.3273 |
|
- Rougel: 56.9984 |
|
- Rougelsum: 59.1424 |
|
|
|
## 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: 5.6e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
|
| No log | 0.91 | 5 | 2.0124 | 53.776 | 46.7427 | 50.7565 | 53.5502 | |
|
| No log | 1.91 | 10 | 1.6353 | 61.8019 | 53.8614 | 58.9744 | 61.339 | |
|
| No log | 2.91 | 15 | 1.5321 | 59.7045 | 51.5968 | 57.0823 | 59.2417 | |
|
| No log | 3.91 | 20 | 1.4569 | 62.4379 | 54.5464 | 59.9202 | 61.9242 | |
|
| 1.5608 | 4.91 | 25 | 1.4613 | 63.3808 | 55.8818 | 61.432 | 63.0208 | |
|
| 1.5608 | 5.91 | 30 | 1.4321 | 59.6761 | 50.9812 | 56.7977 | 59.1214 | |
|
| 1.5608 | 6.91 | 35 | 1.4753 | 62.6439 | 54.7158 | 60.3831 | 62.1046 | |
|
| 1.5608 | 7.91 | 40 | 1.4783 | 60.2735 | 52.7462 | 57.77 | 59.9725 | |
|
| 0.6428 | 8.91 | 45 | 1.4974 | 62.8691 | 54.9062 | 60.3496 | 62.5132 | |
|
| 0.6428 | 9.91 | 50 | 1.5216 | 59.5791 | 51.3273 | 56.9984 | 59.1424 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.15.0 |
|
- Pytorch 1.9.1 |
|
- Datasets 1.18.4 |
|
- Tokenizers 0.10.3 |
|
|
