|
--- |
|
license: apache-2.0 |
|
base_model: google/mt5-small |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: my_mt5_small_test-finetuned-textdetox |
|
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. --> |
|
|
|
# my_mt5_small_test-finetuned-textdetox |
|
|
|
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.1729 |
|
- Rouge1: 48.4128 |
|
- Rouge2: 39.9256 |
|
- Rougel: 48.1823 |
|
- Rougelsum: 48.1665 |
|
- Gen Len: 15.1129 |
|
|
|
## 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: 0.0001 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- 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 | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
|
| 1.4234 | 1.0 | 3480 | 1.3619 | 47.6986 | 39.113 | 47.5064 | 47.4812 | 15.454 | |
|
| 1.3091 | 2.0 | 6960 | 1.2434 | 48.0682 | 39.5031 | 47.8767 | 47.8577 | 15.2398 | |
|
| 1.3695 | 3.0 | 10440 | 1.2162 | 48.1983 | 39.6887 | 47.9807 | 47.9556 | 15.2225 | |
|
| 1.123 | 4.0 | 13920 | 1.1739 | 48.309 | 39.7956 | 48.0868 | 48.0644 | 15.1866 | |
|
| 1.4587 | 5.0 | 17400 | 1.1729 | 48.4128 | 39.9256 | 48.1823 | 48.1665 | 15.1129 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
