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--- |
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license: apache-2.0 |
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base_model: yhavinga/t5-small-24L-ccmatrix-multi |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: final_classifications |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# final_classifications |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1005 |
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- F1: {'f1': 0.9592760180995475} |
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- Precision: {'precision': 0.954954954954955} |
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- Recall: {'recall': 0.9636363636363636} |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------------------:|:---------------------------------:|:------------------------------:| |
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| No log | 1.0 | 110 | 0.2362 | {'f1': 0.0} | {'precision': 0.0} | {'recall': 0.0} | |
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| No log | 2.0 | 220 | 0.1164 | {'f1': 0.9502262443438914} | {'precision': 0.9459459459459459} | {'recall': 0.9545454545454546} | |
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| No log | 3.0 | 330 | 0.0832 | {'f1': 0.9596412556053813} | {'precision': 0.9469026548672567} | {'recall': 0.9727272727272728} | |
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| No log | 4.0 | 440 | 0.0918 | {'f1': 0.9549549549549549} | {'precision': 0.9464285714285714} | {'recall': 0.9636363636363636} | |
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| 0.1554 | 5.0 | 550 | 0.0939 | {'f1': 0.9596412556053813} | {'precision': 0.9469026548672567} | {'recall': 0.9727272727272728} | |
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| 0.1554 | 6.0 | 660 | 0.1005 | {'f1': 0.9592760180995475} | {'precision': 0.954954954954955} | {'recall': 0.9636363636363636} | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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