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---
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: distilbart-cnn-12-6-finetuned-resume-summarizer
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-cnn-12-6-finetuned-resume-summarizer
This model is a fine-tuned version of [Ameer05/model-tokenizer-repo](https://huggingface.co/Ameer05/model-tokenizer-repo) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1123
- Rouge1: 52.5826
- Rouge2: 34.3861
- Rougel: 41.8525
- Rougelsum: 51.0015
## 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: 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 | 3.2243 | 42.8593 | 24.8652 | 34.1789 | 41.406 |
| No log | 1.91 | 10 | 2.6948 | 48.8571 | 28.6711 | 39.2648 | 46.188 |
| No log | 2.91 | 15 | 2.4665 | 50.6085 | 30.4034 | 39.7406 | 48.5449 |
| No log | 3.91 | 20 | 2.3329 | 52.2357 | 32.3398 | 41.574 | 49.4316 |
| 3.6611 | 4.91 | 25 | 2.2362 | 52.0134 | 33.1612 | 41.3103 | 50.255 |
| 3.6611 | 5.91 | 30 | 2.1833 | 51.5434 | 32.7045 | 40.5683 | 49.4238 |
| 3.6611 | 6.91 | 35 | 2.1462 | 53.5144 | 35.4518 | 42.8615 | 51.4053 |
| 3.6611 | 7.91 | 40 | 2.1518 | 52.0985 | 33.6754 | 41.5936 | 50.5159 |
| 2.0326 | 8.91 | 45 | 2.1075 | 53.1401 | 34.9721 | 42.2973 | 51.8454 |
| 2.0326 | 9.91 | 50 | 2.1123 | 52.5826 | 34.3861 | 41.8525 | 51.0015 |
### Framework versions
- Transformers 4.15.0
- Pytorch 1.9.1
- Datasets 2.0.0
- Tokenizers 0.10.3
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