| | --- |
| | license: apache-2.0 |
| | base_model: susnato/ernie-m-base_pytorch |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - f1 |
| | model-index: |
| | - name: 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. --> |
| |
|
| | # Model |
| |
|
| | This model is a fine-tuned version of [susnato/ernie-m-base_pytorch](https://huggingface.co/susnato/ernie-m-base_pytorch) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.6189 |
| | - F1: 0.9294 |
| |
|
| | ## 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 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 32 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 8 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | F1 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:------:| |
| | | 0.2019 | 1.0 | 1500 | 0.1825 | 0.9304 | |
| | | 0.1199 | 2.0 | 3000 | 0.3103 | 0.8986 | |
| | | 0.085 | 3.0 | 4500 | 0.2546 | 0.9268 | |
| | | 0.0516 | 4.0 | 6000 | 0.3140 | 0.9387 | |
| | | 0.0281 | 5.0 | 7500 | 0.6603 | 0.9022 | |
| | | 0.0142 | 6.0 | 9000 | 0.8612 | 0.8931 | |
| | | 0.0068 | 7.0 | 10500 | 0.5700 | 0.9332 | |
| | | 0.002 | 8.0 | 12000 | 0.6189 | 0.9294 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.41.2 |
| | - Pytorch 2.3.0+cu121 |
| | - Datasets 2.19.2 |
| | - Tokenizers 0.19.1 |
| | |
