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--- |
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tags: |
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- summarization |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: distilbart-cnn-12-6-finetuned-resume-summarizer |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# distilbart-cnn-12-6-finetuned-resume-summarizer |
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This model is a fine-tuned version of [Ameer05/model-tokenizer-repo](https://huggingface.co/Ameer05/model-tokenizer-repo) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1123 |
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- Rouge1: 52.5826 |
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- Rouge2: 34.3861 |
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- Rougel: 41.8525 |
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- Rougelsum: 51.0015 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| No log | 0.91 | 5 | 3.2243 | 42.8593 | 24.8652 | 34.1789 | 41.406 | |
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| No log | 1.91 | 10 | 2.6948 | 48.8571 | 28.6711 | 39.2648 | 46.188 | |
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| No log | 2.91 | 15 | 2.4665 | 50.6085 | 30.4034 | 39.7406 | 48.5449 | |
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| No log | 3.91 | 20 | 2.3329 | 52.2357 | 32.3398 | 41.574 | 49.4316 | |
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| 3.6611 | 4.91 | 25 | 2.2362 | 52.0134 | 33.1612 | 41.3103 | 50.255 | |
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| 3.6611 | 5.91 | 30 | 2.1833 | 51.5434 | 32.7045 | 40.5683 | 49.4238 | |
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| 3.6611 | 6.91 | 35 | 2.1462 | 53.5144 | 35.4518 | 42.8615 | 51.4053 | |
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| 3.6611 | 7.91 | 40 | 2.1518 | 52.0985 | 33.6754 | 41.5936 | 50.5159 | |
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| 2.0326 | 8.91 | 45 | 2.1075 | 53.1401 | 34.9721 | 42.2973 | 51.8454 | |
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| 2.0326 | 9.91 | 50 | 2.1123 | 52.5826 | 34.3861 | 41.8525 | 51.0015 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.9.1 |
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- Datasets 2.0.0 |
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- Tokenizers 0.10.3 |
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