|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- swag |
|
model_index: |
|
- name: bert-base-uncased-finetuned-swag |
|
results: |
|
- dataset: |
|
name: swag |
|
type: swag |
|
args: regular |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# bert-base-uncased-finetuned-swag |
|
|
|
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the swag dataset. |
|
It achieves the following results on the evaluation set: |
|
- eval_loss: 0.6189 |
|
- eval_accuracy: 0.7647 |
|
- eval_runtime: 274.5502 |
|
- eval_samples_per_second: 72.868 |
|
- eval_steps_per_second: 4.557 |
|
- epoch: 1.0 |
|
- step: 4597 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 3 |
|
|
|
### Framework versions |
|
|
|
- Transformers 4.9.1 |
|
- Pytorch 1.9.0+cu102 |
|
- Datasets 1.11.0 |
|
- Tokenizers 0.10.3 |
|
|
