|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: distilbert-base-uncased-finetuned-ft1500_reg3 |
|
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. --> |
|
|
|
# distilbert-base-uncased-finetuned-ft1500_reg3 |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7954 |
|
- Mse: 0.7954 |
|
- Mae: 0.6900 |
|
- R2: 0.4769 |
|
- Accuracy: 0.4459 |
|
|
|
## 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: 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: 5 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:--------:| |
|
| 1.018 | 1.0 | 3122 | 0.7491 | 0.7491 | 0.6739 | 0.5073 | 0.4555 | |
|
| 0.668 | 2.0 | 6244 | 0.7397 | 0.7397 | 0.6687 | 0.5135 | 0.4689 | |
|
| 0.4871 | 3.0 | 9366 | 0.7542 | 0.7542 | 0.6730 | 0.5040 | 0.4606 | |
|
| 0.3419 | 4.0 | 12488 | 0.7710 | 0.7710 | 0.6802 | 0.4929 | 0.4536 | |
|
| 0.2532 | 5.0 | 15610 | 0.7954 | 0.7954 | 0.6900 | 0.4769 | 0.4459 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.21.0 |
|
- Pytorch 1.12.0+cu113 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.12.1 |
|
|