| | --- |
| | license: apache-2.0 |
| | base_model: google/flan-t5-small |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: flan-t5-small-comma-correction |
| | 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. --> |
| |
|
| | # flan-t5-small-comma-correction |
| |
|
| | This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0662 |
| | - Gen Len: 39.2167 |
| | - Em Ic: 0.934 |
| | - Em: 0.5759 |
| | - Precision: 0.9177 |
| | - Recall: 0.7736 |
| | - F1: 0.7575 |
| | - Levinstein Ratio: 0.9954 |
| |
|
| | ## 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: 64 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_steps: 200 |
| | - num_epochs: 3.0 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Gen Len | Em Ic | Em | Precision | Recall | F1 | Levinstein Ratio | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:------:|:---------:|:------:|:------:|:----------------:| |
| | | 0.0694 | 1.0 | 2159 | 0.0696 | 39.1396 | 0.9299 | 0.5543 | 0.9178 | 0.7509 | 0.7366 | 0.9951 | |
| | | 0.0558 | 2.0 | 4318 | 0.0670 | 39.1904 | 0.9334 | 0.5736 | 0.9195 | 0.7678 | 0.7537 | 0.9954 | |
| | | 0.0542 | 3.0 | 6477 | 0.0662 | 39.2167 | 0.934 | 0.5759 | 0.9177 | 0.7736 | 0.7575 | 0.9954 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.35.0 |
| | - Pytorch 2.1.0+cu118 |
| | - Datasets 2.14.6 |
| | - Tokenizers 0.14.1 |
| | |
