update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,74 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
tags:
|
| 3 |
+
- summarization
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- rouge
|
| 7 |
+
model-index:
|
| 8 |
+
- name: distilbart-cnn-12-6-finetuned-resume-summarizer
|
| 9 |
+
results: []
|
| 10 |
+
---
|
| 11 |
+
|
| 12 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 13 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 14 |
+
|
| 15 |
+
# distilbart-cnn-12-6-finetuned-resume-summarizer
|
| 16 |
+
|
| 17 |
+
This model is a fine-tuned version of [Ameer05/model-tokenizer-repo](https://huggingface.co/Ameer05/model-tokenizer-repo) on an unknown dataset.
|
| 18 |
+
It achieves the following results on the evaluation set:
|
| 19 |
+
- Loss: 2.1123
|
| 20 |
+
- Rouge1: 52.5826
|
| 21 |
+
- Rouge2: 34.3861
|
| 22 |
+
- Rougel: 41.8525
|
| 23 |
+
- Rougelsum: 51.0015
|
| 24 |
+
|
| 25 |
+
## Model description
|
| 26 |
+
|
| 27 |
+
More information needed
|
| 28 |
+
|
| 29 |
+
## Intended uses & limitations
|
| 30 |
+
|
| 31 |
+
More information needed
|
| 32 |
+
|
| 33 |
+
## Training and evaluation data
|
| 34 |
+
|
| 35 |
+
More information needed
|
| 36 |
+
|
| 37 |
+
## Training procedure
|
| 38 |
+
|
| 39 |
+
### Training hyperparameters
|
| 40 |
+
|
| 41 |
+
The following hyperparameters were used during training:
|
| 42 |
+
- learning_rate: 5e-05
|
| 43 |
+
- train_batch_size: 8
|
| 44 |
+
- eval_batch_size: 8
|
| 45 |
+
- seed: 42
|
| 46 |
+
- gradient_accumulation_steps: 4
|
| 47 |
+
- total_train_batch_size: 32
|
| 48 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 49 |
+
- lr_scheduler_type: linear
|
| 50 |
+
- num_epochs: 10
|
| 51 |
+
- mixed_precision_training: Native AMP
|
| 52 |
+
|
| 53 |
+
### Training results
|
| 54 |
+
|
| 55 |
+
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|
| 56 |
+
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
|
| 57 |
+
| No log | 0.91 | 5 | 3.2243 | 42.8593 | 24.8652 | 34.1789 | 41.406 |
|
| 58 |
+
| No log | 1.91 | 10 | 2.6948 | 48.8571 | 28.6711 | 39.2648 | 46.188 |
|
| 59 |
+
| No log | 2.91 | 15 | 2.4665 | 50.6085 | 30.4034 | 39.7406 | 48.5449 |
|
| 60 |
+
| No log | 3.91 | 20 | 2.3329 | 52.2357 | 32.3398 | 41.574 | 49.4316 |
|
| 61 |
+
| 3.6611 | 4.91 | 25 | 2.2362 | 52.0134 | 33.1612 | 41.3103 | 50.255 |
|
| 62 |
+
| 3.6611 | 5.91 | 30 | 2.1833 | 51.5434 | 32.7045 | 40.5683 | 49.4238 |
|
| 63 |
+
| 3.6611 | 6.91 | 35 | 2.1462 | 53.5144 | 35.4518 | 42.8615 | 51.4053 |
|
| 64 |
+
| 3.6611 | 7.91 | 40 | 2.1518 | 52.0985 | 33.6754 | 41.5936 | 50.5159 |
|
| 65 |
+
| 2.0326 | 8.91 | 45 | 2.1075 | 53.1401 | 34.9721 | 42.2973 | 51.8454 |
|
| 66 |
+
| 2.0326 | 9.91 | 50 | 2.1123 | 52.5826 | 34.3861 | 41.8525 | 51.0015 |
|
| 67 |
+
|
| 68 |
+
|
| 69 |
+
### Framework versions
|
| 70 |
+
|
| 71 |
+
- Transformers 4.15.0
|
| 72 |
+
- Pytorch 1.9.1
|
| 73 |
+
- Datasets 2.0.0
|
| 74 |
+
- Tokenizers 0.10.3
|