metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- Yaxin/SemEval2016Task5Raw
metrics:
- accuracy
base_model: bert-large-uncased
model-index:
- name: bert-large-uncased-semeval2016-laptops
results:
- task:
type: fill-mask
name: Masked Language Modeling
dataset:
name: Yaxin/SemEval2016Task5Raw laptops_english
type: Yaxin/SemEval2016Task5Raw
config: laptops_english
split: validation
args: laptops_english
metrics:
- type: accuracy
value: 0.7432432432432432
name: Accuracy
bert-large-uncased-semeval2016-laptops
This model is a fine-tuned version of bert-large-uncased on the Yaxin/SemEval2016Task5Raw laptops_english dataset. It achieves the following results on the evaluation set:
- Loss: 0.9255
- Accuracy: 0.7432
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: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30.0
Training results
Framework versions
- Transformers 4.29.0.dev0
- Pytorch 1.13.0
- Datasets 2.11.0
- Tokenizers 0.13.2