|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: distilbert-base-uncased |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: bert_interview_new |
|
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_interview_new |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.6712 |
|
- Accuracy: 0.3534 |
|
|
|
## 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: 1e-05 |
|
- train_batch_size: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- 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: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| No log | 1.0 | 463 | 2.2196 | 0.3319 | |
|
| 2.1608 | 2.0 | 926 | 2.1235 | 0.3534 | |
|
| 1.816 | 3.0 | 1389 | 2.1393 | 0.3879 | |
|
| 1.533 | 4.0 | 1852 | 2.1836 | 0.3578 | |
|
| 1.2761 | 5.0 | 2315 | 2.2730 | 0.3664 | |
|
| 1.122 | 6.0 | 2778 | 2.3939 | 0.3578 | |
|
| 0.9403 | 7.0 | 3241 | 2.4908 | 0.3578 | |
|
| 0.8317 | 8.0 | 3704 | 2.5671 | 0.3448 | |
|
| 0.7571 | 9.0 | 4167 | 2.6484 | 0.3491 | |
|
| 0.693 | 10.0 | 4630 | 2.6712 | 0.3534 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.47.1 |
|
- Pytorch 2.5.1+cu121 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.21.0 |
|
|