|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: t5-small-med-term-mlm |
|
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. --> |
|
|
|
# t5-small-med-term-mlm |
|
|
|
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4736 |
|
- Rouge2 Precision: 0.7731 |
|
- Rouge2 Recall: 0.5541 |
|
- Rouge2 Fmeasure: 0.6251 |
|
|
|
## 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: 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: 4 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | |
|
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:| |
|
| 0.6498 | 1.0 | 15827 | 0.5480 | 0.7629 | 0.5457 | 0.6161 | |
|
| 0.5674 | 2.0 | 31654 | 0.4989 | 0.7697 | 0.551 | 0.622 | |
|
| 0.5631 | 3.0 | 47481 | 0.4795 | 0.7726 | 0.5541 | 0.625 | |
|
| 0.534 | 4.0 | 63308 | 0.4736 | 0.7731 | 0.5541 | 0.6251 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.17.0 |
|
- Pytorch 1.10.0+cu111 |
|
- Datasets 1.18.4 |
|
- Tokenizers 0.11.6 |
|
|
