|
--- |
|
language: |
|
- en |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- glue |
|
metrics: |
|
- accuracy |
|
- f1 |
|
model-index: |
|
- name: add_BERT_no_pretrain_mrpc |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: GLUE MRPC |
|
type: glue |
|
config: mrpc |
|
split: validation |
|
args: mrpc |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.696078431372549 |
|
- name: F1 |
|
type: f1 |
|
value: 0.7933333333333332 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# add_BERT_no_pretrain_mrpc |
|
|
|
This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE MRPC dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5912 |
|
- Accuracy: 0.6961 |
|
- F1: 0.7933 |
|
- Combined Score: 0.7447 |
|
|
|
## 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: 4e-05 |
|
- train_batch_size: 128 |
|
- eval_batch_size: 128 |
|
- seed: 10 |
|
- distributed_type: multi-GPU |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 50 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:| |
|
| 0.6854 | 1.0 | 29 | 0.6711 | 0.6838 | 0.8122 | 0.7480 | |
|
| 0.6496 | 2.0 | 58 | 0.6802 | 0.6838 | 0.8122 | 0.7480 | |
|
| 0.648 | 3.0 | 87 | 0.6246 | 0.6838 | 0.8122 | 0.7480 | |
|
| 0.6363 | 4.0 | 116 | 0.6174 | 0.6838 | 0.8122 | 0.7480 | |
|
| 0.6049 | 5.0 | 145 | 0.6176 | 0.6593 | 0.7459 | 0.7026 | |
|
| 0.5491 | 6.0 | 174 | 0.6038 | 0.6814 | 0.7950 | 0.7382 | |
|
| 0.5601 | 7.0 | 203 | 0.5912 | 0.6961 | 0.7933 | 0.7447 | |
|
| 0.5505 | 8.0 | 232 | 0.6346 | 0.6716 | 0.7781 | 0.7249 | |
|
| 0.5327 | 9.0 | 261 | 0.6283 | 0.6544 | 0.7531 | 0.7037 | |
|
| 0.529 | 10.0 | 290 | 0.6341 | 0.6520 | 0.7568 | 0.7044 | |
|
| 0.5337 | 11.0 | 319 | 0.6285 | 0.6618 | 0.7579 | 0.7098 | |
|
| 0.5383 | 12.0 | 348 | 0.6322 | 0.6348 | 0.7286 | 0.6817 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.30.2 |
|
- Pytorch 1.14.0a0+410ce96 |
|
- Datasets 2.12.0 |
|
- Tokenizers 0.13.3 |
|
|
