| | --- |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: gpt2_small_summarized |
| | 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. --> |
| |
|
| | # gpt2_small_summarized |
| |
|
| | This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 3.6935 |
| | - Accuracy: 0.79 |
| | - Precision: 0.2632 |
| | - Recall: 0.1515 |
| | - F1: 0.1923 |
| | - D-index: 1.4571 |
| |
|
| | ## 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: 4 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 1600 |
| | - num_epochs: 20 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | D-index | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:| |
| | | No log | 1.0 | 200 | 0.9451 | 0.77 | 0.0667 | 0.0303 | 0.0417 | 1.3827 | |
| | | No log | 2.0 | 400 | 0.7625 | 0.81 | 0.0 | 0.0 | 0.0 | 1.4265 | |
| | | 2.1174 | 3.0 | 600 | 0.7145 | 0.835 | 0.0 | 0.0 | 0.0 | 1.4607 | |
| | | 2.1174 | 4.0 | 800 | 1.0087 | 0.835 | 0.0 | 0.0 | 0.0 | 1.4607 | |
| | | 0.6744 | 5.0 | 1000 | 0.6728 | 0.825 | 0.0 | 0.0 | 0.0 | 1.4471 | |
| | | 0.6744 | 6.0 | 1200 | 0.7295 | 0.725 | 0.1944 | 0.2121 | 0.2029 | 1.3899 | |
| | | 0.6744 | 7.0 | 1400 | 2.0423 | 0.825 | 0.3333 | 0.0606 | 0.1026 | 1.4704 | |
| | | 0.3582 | 8.0 | 1600 | 2.5923 | 0.685 | 0.1591 | 0.2121 | 0.1818 | 1.3332 | |
| | | 0.3582 | 9.0 | 1800 | 2.9312 | 0.605 | 0.1974 | 0.4545 | 0.2752 | 1.3098 | |
| | | 0.1089 | 10.0 | 2000 | 3.0778 | 0.81 | 0.0 | 0.0 | 0.0 | 1.4265 | |
| | | 0.1089 | 11.0 | 2200 | 3.0158 | 0.785 | 0.25 | 0.1515 | 0.1887 | 1.4503 | |
| | | 0.1089 | 12.0 | 2400 | 3.0195 | 0.8 | 0.3333 | 0.2121 | 0.2593 | 1.4934 | |
| | | 0.0376 | 13.0 | 2600 | 3.3198 | 0.77 | 0.2593 | 0.2121 | 0.2333 | 1.4525 | |
| | | 0.0376 | 14.0 | 2800 | 3.4092 | 0.77 | 0.2593 | 0.2121 | 0.2333 | 1.4525 | |
| | | 0.0012 | 15.0 | 3000 | 3.5722 | 0.76 | 0.2 | 0.1515 | 0.1724 | 1.4157 | |
| | | 0.0012 | 16.0 | 3200 | 3.5919 | 0.775 | 0.25 | 0.1818 | 0.2105 | 1.4480 | |
| | | 0.0012 | 17.0 | 3400 | 3.5835 | 0.795 | 0.2778 | 0.1515 | 0.1961 | 1.4639 | |
| | | 0.0045 | 18.0 | 3600 | 3.6829 | 0.785 | 0.25 | 0.1515 | 0.1887 | 1.4503 | |
| | | 0.0045 | 19.0 | 3800 | 3.6905 | 0.785 | 0.25 | 0.1515 | 0.1887 | 1.4503 | |
| | | 0.0008 | 20.0 | 4000 | 3.6935 | 0.79 | 0.2632 | 0.1515 | 0.1923 | 1.4571 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.28.0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.12.0 |
| | - Tokenizers 0.13.3 |
| | |
