| | --- |
| | license: apache-2.0 |
| | base_model: yhavinga/t5-small-24L-ccmatrix-multi |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - f1 |
| | - precision |
| | - recall |
| | model-index: |
| | - name: final_classifications |
| | 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. --> |
| |
|
| | # final_classifications |
| | |
| | This model is a fine-tuned version of [yhavinga/t5-small-24L-ccmatrix-multi](https://huggingface.co/yhavinga/t5-small-24L-ccmatrix-multi) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1005 |
| | - F1: {'f1': 0.9592760180995475} |
| | - Precision: {'precision': 0.954954954954955} |
| | - Recall: {'recall': 0.9636363636363636} |
| | |
| | ## 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: 0.0001 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 6 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------------------------:|:---------------------------------:|:------------------------------:| |
| | | No log | 1.0 | 110 | 0.2362 | {'f1': 0.0} | {'precision': 0.0} | {'recall': 0.0} | |
| | | No log | 2.0 | 220 | 0.1164 | {'f1': 0.9502262443438914} | {'precision': 0.9459459459459459} | {'recall': 0.9545454545454546} | |
| | | No log | 3.0 | 330 | 0.0832 | {'f1': 0.9596412556053813} | {'precision': 0.9469026548672567} | {'recall': 0.9727272727272728} | |
| | | No log | 4.0 | 440 | 0.0918 | {'f1': 0.9549549549549549} | {'precision': 0.9464285714285714} | {'recall': 0.9636363636363636} | |
| | | 0.1554 | 5.0 | 550 | 0.0939 | {'f1': 0.9596412556053813} | {'precision': 0.9469026548672567} | {'recall': 0.9727272727272728} | |
| | | 0.1554 | 6.0 | 660 | 0.1005 | {'f1': 0.9592760180995475} | {'precision': 0.954954954954955} | {'recall': 0.9636363636363636} | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.40.1 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.19.0 |
| | - Tokenizers 0.19.1 |
| | |
