|
|
--- |
|
|
license: apache-2.0 |
|
|
base_model: bert-base-uncased |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
datasets: |
|
|
- bigbench |
|
|
metrics: |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: bigbench_entailedpolarity-bert-base-uncased |
|
|
results: |
|
|
- task: |
|
|
name: Text Classification |
|
|
type: text-classification |
|
|
dataset: |
|
|
name: bigbench |
|
|
type: bigbench |
|
|
config: entailed_polarity |
|
|
split: train |
|
|
args: entailed_polarity |
|
|
metrics: |
|
|
- name: Accuracy |
|
|
type: accuracy |
|
|
value: 0.9583333333333334 |
|
|
--- |
|
|
|
|
|
<!-- 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. --> |
|
|
|
|
|
# bigbench_entailedpolarity-bert-base-uncased |
|
|
|
|
|
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the bigbench dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.3706 |
|
|
- Accuracy: 0.9583 |
|
|
|
|
|
## 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: 5e-05 |
|
|
- train_batch_size: 4 |
|
|
- eval_batch_size: 32 |
|
|
- seed: 42 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 20 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
|
| No log | 1.0 | 24 | 0.5613 | 0.7917 | |
|
|
| No log | 2.0 | 48 | 0.5337 | 0.7917 | |
|
|
| No log | 3.0 | 72 | 0.3178 | 0.875 | |
|
|
| No log | 4.0 | 96 | 0.1924 | 0.9167 | |
|
|
| No log | 5.0 | 120 | 0.2007 | 0.9583 | |
|
|
| No log | 6.0 | 144 | 0.2766 | 0.9583 | |
|
|
| No log | 7.0 | 168 | 0.3031 | 0.9583 | |
|
|
| No log | 8.0 | 192 | 0.3291 | 0.9583 | |
|
|
| No log | 9.0 | 216 | 0.3381 | 0.9583 | |
|
|
| No log | 10.0 | 240 | 0.3454 | 0.9583 | |
|
|
| No log | 11.0 | 264 | 0.3508 | 0.9583 | |
|
|
| No log | 12.0 | 288 | 0.3554 | 0.9583 | |
|
|
| No log | 13.0 | 312 | 0.3592 | 0.9583 | |
|
|
| No log | 14.0 | 336 | 0.3624 | 0.9583 | |
|
|
| No log | 15.0 | 360 | 0.3650 | 0.9583 | |
|
|
| No log | 16.0 | 384 | 0.3671 | 0.9583 | |
|
|
| No log | 17.0 | 408 | 0.3686 | 0.9583 | |
|
|
| No log | 18.0 | 432 | 0.3696 | 0.9583 | |
|
|
| No log | 19.0 | 456 | 0.3704 | 0.9583 | |
|
|
| No log | 20.0 | 480 | 0.3706 | 0.9583 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.35.2 |
|
|
- Pytorch 1.10.1+cu102 |
|
|
- Datasets 2.15.0 |
|
|
- Tokenizers 0.15.0 |
|
|
|
