| | --- |
| | license: apache-2.0 |
| | tags: |
| | - summarization |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: easyTermsSummerizer |
| | results: [] |
| | datasets: |
| | - Quake24/paraphrasedPayPal |
| | - Quake24/paraphrasedTwitter |
| | language: |
| | - en |
| | library_name: transformers |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # easyTermsSummerizer |
| |
|
| | This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.8124 |
| | - Rouge1: 0.7533 |
| | - Rouge2: 0.6964 |
| | - Rougel: 0.6806 |
| | - Rougelsum: 0.6793 |
| |
|
| | ## 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: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 3.0 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
| | | No log | 1.0 | 2 | 2.2083 | 0.7332 | 0.6595 | 0.6374 | 0.6376 | |
| | | No log | 2.0 | 4 | 1.9331 | 0.7776 | 0.7268 | 0.6991 | 0.7005 | |
| | | No log | 3.0 | 6 | 1.8124 | 0.7533 | 0.6964 | 0.6806 | 0.6793 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.27.3 |
| | - Pytorch 1.13.0 |
| | - Datasets 2.1.0 |
| | - Tokenizers 0.13.2 |
| | # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
| | Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Quake24__easyTermsSummerizer) |
| |
|
| | | Metric | Value | |
| | |-----------------------|---------------------------| |
| | | Avg. | 24.73 | |
| | | ARC (25-shot) | 25.77 | |
| | | HellaSwag (10-shot) | 25.81 | |
| | | MMLU (5-shot) | 23.12 | |
| | | TruthfulQA (0-shot) | 47.69 | |
| | | Winogrande (5-shot) | 50.75 | |
| | | GSM8K (5-shot) | 0.0 | |
| | | DROP (3-shot) | 0.01 | |
| |
|
