multi_task_model_content
This model is a fine-tuned version of RonTon05/model_content_V2_test on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9316
- Accuracy: 0.6755
- F1: 0.4286
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.3757 | 1.0 | 330 | 1.2561 | 0.4734 | 0.1465 |
| 1.2316 | 2.0 | 660 | 1.1385 | 0.5831 | 0.2662 |
| 1.1559 | 3.0 | 990 | 1.0708 | 0.6375 | 0.3607 |
| 1.1027 | 4.0 | 1320 | 1.0156 | 0.6637 | 0.4096 |
| 1.0688 | 5.0 | 1650 | 0.9840 | 0.6608 | 0.4077 |
| 1.0474 | 6.0 | 1980 | 0.9621 | 0.6709 | 0.4164 |
| 1.0314 | 7.0 | 2310 | 0.9583 | 0.6645 | 0.4103 |
| 1.0212 | 8.0 | 2640 | 0.9407 | 0.6745 | 0.4258 |
| 1.0097 | 9.0 | 2970 | 0.9329 | 0.6758 | 0.4305 |
| 1.0096 | 10.0 | 3300 | 0.9316 | 0.6755 | 0.4286 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.6.0+cu124
- Datasets 4.4.1
- Tokenizers 0.22.1
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