|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- nyu-mll/glue |
|
metrics: |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: glue_sst_classifier |
|
results: |
|
- task: |
|
type: text-classification |
|
name: Text Classification |
|
dataset: |
|
name: glue |
|
type: glue |
|
args: sst2 |
|
metrics: |
|
- type: f1 |
|
value: 0.9033707865168539 |
|
name: F1 |
|
- type: accuracy |
|
value: 0.9013761467889908 |
|
name: Accuracy |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# glue_sst_classifier |
|
|
|
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the glue dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2359 |
|
- F1: 0.9034 |
|
- Accuracy: 0.9014 |
|
|
|
## 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: 1e-05 |
|
- train_batch_size: 128 |
|
- eval_batch_size: 128 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 1.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:| |
|
| 0.3653 | 0.19 | 100 | 0.3213 | 0.8717 | 0.8727 | |
|
| 0.291 | 0.38 | 200 | 0.2662 | 0.8936 | 0.8911 | |
|
| 0.2239 | 0.57 | 300 | 0.2417 | 0.9081 | 0.9060 | |
|
| 0.2306 | 0.76 | 400 | 0.2359 | 0.9105 | 0.9094 | |
|
| 0.2185 | 0.95 | 500 | 0.2371 | 0.9011 | 0.8991 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.18.0 |
|
- Pytorch 1.11.0+cu113 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.12.1 |
|
|
