|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- f1 |
|
model-index: |
|
- name: bert-nlp-project-ft-imdb-ds-google |
|
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-nlp-project-ft-imdb-ds-google |
|
|
|
This model is a fine-tuned version of [jestemleon/bert-nlp-project-imdb](https://huggingface.co/jestemleon/bert-nlp-project-imdb) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3097 |
|
- Accuracy: 0.9124 |
|
- F1: 0.9197 |
|
|
|
## 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: 2e-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 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
|
| 0.3517 | 0.37 | 196 | 0.2556 | 0.9105 | 0.9187 | |
|
| 0.27 | 0.75 | 392 | 0.2369 | 0.9038 | 0.9105 | |
|
| 0.2246 | 1.12 | 588 | 0.2630 | 0.9133 | 0.9205 | |
|
| 0.1869 | 1.49 | 784 | 0.2885 | 0.9038 | 0.9071 | |
|
| 0.1696 | 1.86 | 980 | 0.2811 | 0.9152 | 0.9233 | |
|
| 0.1474 | 2.24 | 1176 | 0.2918 | 0.9190 | 0.9243 | |
|
| 0.1187 | 2.61 | 1372 | 0.3045 | 0.9133 | 0.9212 | |
|
| 0.1077 | 2.98 | 1568 | 0.3097 | 0.9124 | 0.9197 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.25.1 |
|
- Pytorch 1.13.0+cu116 |
|
- Datasets 2.8.0 |
|
- Tokenizers 0.13.2 |
|
|
