fine_tuned_yelp
This model is a fine-tuned version of Qwen/Qwen2-1.5B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2855
- Accuracy: 0.9328
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.927 | 0.0170 | 100 | 0.4956 | 0.7806 |
0.5634 | 0.0340 | 200 | 0.4637 | 0.8044 |
0.4876 | 0.0509 | 300 | 0.7024 | 0.8648 |
0.4179 | 0.0679 | 400 | 0.3941 | 0.8944 |
0.4397 | 0.0849 | 500 | 0.5622 | 0.8291 |
0.3985 | 0.1019 | 600 | 0.3185 | 0.8997 |
0.4607 | 0.1188 | 700 | 0.4404 | 0.8942 |
0.4023 | 0.1358 | 800 | 0.2967 | 0.9091 |
0.3185 | 0.1528 | 900 | 0.3033 | 0.8980 |
0.335 | 0.1698 | 1000 | 0.2653 | 0.9232 |
0.3665 | 0.1868 | 1100 | 0.2280 | 0.9246 |
0.3033 | 0.2037 | 1200 | 0.1975 | 0.9320 |
0.2578 | 0.2207 | 1300 | 0.2171 | 0.9341 |
0.3417 | 0.2377 | 1400 | 0.2497 | 0.9301 |
0.3222 | 0.2547 | 1500 | 0.2855 | 0.9328 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu126
- Datasets 3.3.2
- Tokenizers 0.21.0
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Base model
Qwen/Qwen2-1.5B