|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: google/mt5-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
- bleu |
|
model-index: |
|
- name: mt5-base-qaqg-finetuned-SQuAD-id-ir |
|
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-base-qaqg-finetuned-SQuAD-id-ir |
|
|
|
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.2951 |
|
- Rouge1: 0.4537 |
|
- Rouge2: 0.2692 |
|
- Rougel: 0.4120 |
|
- Rougelsum: 0.4144 |
|
- Bleu: 0.2295 |
|
|
|
## 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 | Bleu | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:------:| |
|
| 1.5663 | 1.0 | 2000 | 1.4508 | 0.4214 | 0.2349 | 0.3787 | 0.3812 | 0.2152 | |
|
| 1.3135 | 2.0 | 4000 | 1.3187 | 0.4432 | 0.2562 | 0.4011 | 0.4033 | 0.2262 | |
|
| 1.1748 | 3.0 | 6000 | 1.2928 | 0.4482 | 0.2641 | 0.4070 | 0.4097 | 0.2255 | |
|
| 1.1115 | 4.0 | 8000 | 1.2927 | 0.4543 | 0.2714 | 0.4128 | 0.4150 | 0.2293 | |
|
| 1.0387 | 5.0 | 10000 | 1.2951 | 0.4537 | 0.2692 | 0.4120 | 0.4144 | 0.2295 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.2 |
|
- Pytorch 2.4.0a0+f70bd71a48.nv24.06 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
