| | --- |
| | license: apache-2.0 |
| | base_model: google/t5-efficient-tiny |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: denoice-finetuned-xsum |
| | 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. --> |
| |
|
| | # denoice-finetuned-xsum |
| |
|
| | This model is a fine-tuned version of [google/t5-efficient-tiny](https://huggingface.co/google/t5-efficient-tiny) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7541 |
| | - Rouge1: 76.26 |
| | - Rouge2: 61.8085 |
| | - Rougel: 76.1635 |
| | - Rougelsum: 76.1928 |
| | - Gen Len: 17.4843 |
| |
|
| | ## 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: 2e-05 |
| | - train_batch_size: 500 |
| | - eval_batch_size: 500 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 5 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
| | | No log | 1.0 | 76 | 0.7604 | 75.9742 | 61.5113 | 75.8301 | 75.8438 | 17.4817 | |
| | | No log | 2.0 | 152 | 0.7574 | 75.9172 | 61.56 | 75.7901 | 75.8489 | 17.4817 | |
| | | No log | 3.0 | 228 | 0.7568 | 76.382 | 61.5593 | 76.1883 | 76.2735 | 17.4791 | |
| | | No log | 4.0 | 304 | 0.7565 | 76.3074 | 61.8211 | 76.1848 | 76.2148 | 17.4843 | |
| | | No log | 5.0 | 380 | 0.7541 | 76.26 | 61.8085 | 76.1635 | 76.1928 | 17.4843 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.36.2 |
| | - Pytorch 1.13.1 |
| | - Datasets 2.16.1 |
| | - Tokenizers 0.15.0 |
| |
|
