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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- Yaxin/SemEval2014Task4Raw
metrics:
- accuracy
model-index:
- name: bert-base-uncased-semeval2014
results:
- task:
name: Masked Language Modeling
type: fill-mask
dataset:
name: Yaxin/SemEval2014Task4Raw All
type: Yaxin/SemEval2014Task4Raw
config: All
split: validation
args: All
metrics:
- name: Accuracy
type: accuracy
value: 0.8395989974937343
---
<!-- 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-semeval2014
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the Yaxin/SemEval2014Task4Raw All dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7027
- Accuracy: 0.8396
## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100.0
### Training results
### Framework versions
- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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