|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: distilbert-base-uncased |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: distilbert-base-uncased-distilled-clinc |
|
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-distilled-clinc |
|
|
|
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: 0.3223 |
|
- Accuracy: 0.9461 |
|
|
|
## 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: 48 |
|
- eval_batch_size: 48 |
|
- seed: 42 |
|
- optimizer: Use OptimizerNames.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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 2.8424 | 1.0 | 318 | 2.0795 | 0.7271 | |
|
| 1.6103 | 2.0 | 636 | 1.0650 | 0.8577 | |
|
| 0.8466 | 3.0 | 954 | 0.6074 | 0.9135 | |
|
| 0.4999 | 4.0 | 1272 | 0.4376 | 0.9310 | |
|
| 0.3539 | 5.0 | 1590 | 0.3770 | 0.9397 | |
|
| 0.2899 | 6.0 | 1908 | 0.3515 | 0.9419 | |
|
| 0.2589 | 7.0 | 2226 | 0.3353 | 0.9448 | |
|
| 0.2418 | 8.0 | 2544 | 0.3276 | 0.9458 | |
|
| 0.2319 | 9.0 | 2862 | 0.3234 | 0.9458 | |
|
| 0.2284 | 10.0 | 3180 | 0.3223 | 0.9461 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.47.1 |
|
- Pytorch 2.5.1+cu124 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.21.0 |
|
|
