|
--- |
|
license: apache-2.0 |
|
base_model: google/mt5-small |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: mt5-small-finetuned-b8-10-local |
|
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. --> |
|
|
|
# mt5-small-finetuned-b8-10-local |
|
|
|
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: 3.5178 |
|
- Rouge-1: 22.6249 |
|
- Rouge-2: 7.9752 |
|
- Rouge-l: 20.3546 |
|
- Gen Len: 17.0843 |
|
|
|
## 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: 1 |
|
- eval_batch_size: 1 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 16 |
|
- total_train_batch_size: 16 |
|
- optimizer: Adafactor |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Gen Len | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | |
|
|:-------------:|:-----:|:-----:|:-------:|:---------------:|:-------:|:-------:|:-------:| |
|
| 5.111 | 1.0 | 1356 | 12.3837 | 4.0081 | 18.105 | 6.0904 | 16.8637 | |
|
| 4.5548 | 2.0 | 2712 | 3.8803 | 19.8119 | 6.9894 | 18.2397 | 14.1547 | |
|
| 4.3667 | 3.0 | 4069 | 3.7301 | 21.0826 | 7.3597 | 19.1813 | 16.1043 | |
|
| 4.1807 | 4.0 | 5426 | 3.6560 | 21.6212 | 7.5877 | 19.5831 | 16.7592 | |
|
| 4.1524 | 5.0 | 6783 | 3.5911 | 22.0587 | 7.6506 | 19.9304 | 16.7987 | |
|
| 4.1061 | 6.0 | 8140 | 3.5603 | 22.1661 | 7.7772 | 19.9915 | 16.8959 | |
|
| 4.0028 | 7.0 | 9497 | 3.5431 | 22.6005 | 7.9698 | 20.3279 | 16.9174 | |
|
| 3.9558 | 8.0 | 10854 | 3.5305 | 22.6074 | 7.9613 | 20.3267 | 17.0914 | |
|
| 3.9647 | 9.0 | 12211 | 3.5207 | 22.5858 | 7.947 | 20.2764 | 17.0981 | |
|
| 4.0044 | 9.99 | 13560 | 3.5178 | 22.6249 | 7.9752 | 20.3546 | 17.0843 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.0 |
|
- Pytorch 1.13.1+cu116 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.14.1 |
|
|
