| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: EN_mt5-base_5_spider |
| | 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. --> |
| |
|
| | # EN_mt5-base_5_spider |
| | |
| | This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.0147 |
| | - Rouge2 Precision: 0.0101 |
| | - Rouge2 Recall: 0.0008 |
| | - Rouge2 Fmeasure: 0.0014 |
| | |
| | ## 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: 5 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | |
| | |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:| |
| | | No log | 1.0 | 438 | 4.4261 | 0.0037 | 0.0008 | 0.0013 | |
| | | 13.8978 | 2.0 | 876 | 1.9847 | 0.0032 | 0.0012 | 0.0016 | |
| | | 3.4854 | 3.0 | 1314 | 1.6748 | 0.0002 | 0.0 | 0.0 | |
| | | 2.1063 | 4.0 | 1752 | 1.2913 | 0.0074 | 0.0029 | 0.0036 | |
| | | 1.6372 | 5.0 | 2190 | 1.0147 | 0.0101 | 0.0008 | 0.0014 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.26.1 |
| | - Pytorch 2.0.1+cu117 |
| | - Datasets 2.14.7.dev0 |
| | - Tokenizers 0.13.3 |
| | |
