|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: mt5-small-query_realestate_cars-finetuned |
|
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-query_realestate_cars-finetuned |
|
|
|
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2111 |
|
- Rouge1: 51.6261 |
|
- Rouge2: 40.1355 |
|
- Rougel: 51.6277 |
|
- Rougelsum: 51.6154 |
|
- Gen Len: 8.9971 |
|
- Valid Json: 0.0085 |
|
|
|
## 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: 0.0002 |
|
- train_batch_size: 4 |
|
- eval_batch_size: 4 |
|
- 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 | Valid Json | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:----------:| |
|
| 0.4256 | 1.0 | 12204 | 0.2693 | 50.0289 | 38.3453 | 50.0269 | 50.027 | 8.9965 | 0.0061 | |
|
| 0.3171 | 2.0 | 24408 | 0.2338 | 50.1782 | 38.5868 | 50.1546 | 50.1534 | 8.9985 | 0.0053 | |
|
| 0.2364 | 3.0 | 36612 | 0.2200 | 51.1478 | 39.5229 | 51.1357 | 51.1351 | 8.9978 | 0.0068 | |
|
| 0.1869 | 4.0 | 48816 | 0.2130 | 51.603 | 39.91 | 51.5963 | 51.5877 | 8.9974 | 0.0088 | |
|
| 0.2221 | 5.0 | 61020 | 0.2111 | 51.6261 | 40.1355 | 51.6277 | 51.6154 | 8.9971 | 0.0085 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.24.0 |
|
- Pytorch 1.13.0+cu117 |
|
- Datasets 2.8.0 |
|
- Tokenizers 0.12.1 |
|
|
