|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: google/bert_uncased_L-4_H-256_A-4 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: bert_uncased_L-4_H-256_A-4_sst2 |
|
results: [] |
|
--- |
|
|
|
<!-- 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_uncased_L-4_H-256_A-4_sst2 |
|
|
|
This model is a fine-tuned version of [google/bert_uncased_L-4_H-256_A-4](https://huggingface.co/google/bert_uncased_L-4_H-256_A-4) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4575 |
|
- Accuracy: 0.8589 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.4143 | 1.0 | 264 | 0.4119 | 0.8131 | |
|
| 0.2672 | 2.0 | 528 | 0.3628 | 0.8429 | |
|
| 0.2117 | 3.0 | 792 | 0.3785 | 0.8498 | |
|
| 0.1736 | 4.0 | 1056 | 0.4139 | 0.8475 | |
|
| 0.1493 | 5.0 | 1320 | 0.4231 | 0.8532 | |
|
| 0.1294 | 6.0 | 1584 | 0.4411 | 0.8544 | |
|
| 0.1159 | 7.0 | 1848 | 0.4575 | 0.8589 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.46.3 |
|
- Pytorch 2.2.1+cu118 |
|
- Datasets 2.17.0 |
|
- Tokenizers 0.20.3 |
|
|