| --- |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: distilbert-base-uncased-Distilbert-Model |
| 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-Distilbert-Model |
|
|
| 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: 0.7456 |
| - F1: 0.7245 |
|
|
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | 0.8394 | 0.5 | 500 | 0.8400 | 0.6557 | |
| | 0.7944 | 1.0 | 1000 | 0.7827 | 0.6959 | |
| | 0.7253 | 1.5 | 1500 | 0.7619 | 0.6763 | |
| | 0.6838 | 2.01 | 2000 | 0.7456 | 0.7245 | |
| | 0.5503 | 2.51 | 2500 | 0.7754 | 0.7117 | |
| | 0.5517 | 3.01 | 3000 | 0.7592 | 0.7199 | |
| | 0.4178 | 3.51 | 3500 | 0.9776 | 0.7145 | |
| | 0.4225 | 4.01 | 4000 | 1.1820 | 0.7055 | |
| | 0.3327 | 4.51 | 4500 | 1.3212 | 0.7038 | |
| | 0.3292 | 5.02 | 5000 | 1.4429 | 0.7057 | |
| | 0.2563 | 5.52 | 5500 | 1.5018 | 0.7049 | |
| | 0.2555 | 6.02 | 6000 | 1.4722 | 0.7025 | |
| | 0.1745 | 6.52 | 6500 | 1.7254 | 0.7035 | |
| | 0.1813 | 7.02 | 7000 | 1.7894 | 0.6957 | |
| | 0.1473 | 7.52 | 7500 | 1.9552 | 0.6947 | |
| | 0.1381 | 8.02 | 8000 | 1.9619 | 0.7022 | |
| | 0.1003 | 8.53 | 8500 | 2.0648 | 0.6982 | |
| | 0.0916 | 9.03 | 9000 | 2.1473 | 0.6945 | |
| | 0.0779 | 9.53 | 9500 | 2.1930 | 0.6947 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.33.1 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.5 |
| - Tokenizers 0.13.3 |
|
|
