metadata
library_name: transformers
license: apache-2.0
base_model: google/bert_uncased_L-4_H-128_A-2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_uncased_L-4_H-128_A-2_wnli
results: []
bert_uncased_L-4_H-128_A-2_wnli
This model is a fine-tuned version of google/bert_uncased_L-4_H-128_A-2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7140
- Accuracy: 0.3239
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: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6968 | 1.0 | 3 | 0.7060 | 0.4225 |
| 0.6898 | 2.0 | 6 | 0.7042 | 0.3521 |
| 0.6912 | 3.0 | 9 | 0.7055 | 0.3662 |
| 0.695 | 4.0 | 12 | 0.7075 | 0.3380 |
| 0.6946 | 5.0 | 15 | 0.7099 | 0.3099 |
| 0.6921 | 6.0 | 18 | 0.7122 | 0.3099 |
| 0.6874 | 7.0 | 21 | 0.7140 | 0.3239 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3