| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: EN_mt5-base_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_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: 1.8036 |
| | - Rouge2 Precision: 0.0 |
| | - Rouge2 Recall: 0.0 |
| | - Rouge2 Fmeasure: 0.0 |
| |
|
| | ## 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: 15 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | |
| | |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:| |
| | | No log | 1.0 | 438 | 0.2132 | 0.009 | 0.0041 | 0.0051 | |
| | | 6.2612 | 2.0 | 876 | 0.5214 | 0.0036 | 0.0013 | 0.0018 | |
| | | 0.161 | 3.0 | 1314 | 0.4509 | 0.009 | 0.0038 | 0.0051 | |
| | | 0.0989 | 4.0 | 1752 | 0.4065 | 0.0 | 0.0 | 0.0 | |
| | | 0.0793 | 5.0 | 2190 | 0.3735 | 0.0 | 0.0 | 0.0 | |
| | | 0.0657 | 6.0 | 2628 | 0.3679 | 0.0 | 0.0 | 0.0 | |
| | | 0.0592 | 7.0 | 3066 | 0.3044 | 0.0016 | 0.0008 | 0.001 | |
| | | 0.0557 | 8.0 | 3504 | 0.3032 | 0.0 | 0.0 | 0.0 | |
| | | 0.0557 | 9.0 | 3942 | 0.3212 | 0.0014 | 0.002 | 0.0015 | |
| | | 0.7984 | 10.0 | 4380 | 0.7433 | 0.0 | 0.0 | 0.0 | |
| | | 0.9026 | 11.0 | 4818 | 0.0904 | 0.0 | 0.0 | 0.0 | |
| | | 0.0419 | 12.0 | 5256 | 2.8192 | 0.0 | 0.0 | 0.0 | |
| | | 0.0184 | 13.0 | 5694 | 0.7313 | 0.0 | 0.0 | 0.0 | |
| | | 0.0121 | 14.0 | 6132 | 0.9688 | 0.0 | 0.0 | 0.0 | |
| | | 0.0116 | 15.0 | 6570 | 1.8036 | 0.0 | 0.0 | 0.0 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.26.1 |
| | - Pytorch 2.0.1+cu117 |
| | - Datasets 2.14.7.dev0 |
| | - Tokenizers 0.13.3 |
| |
|
