soda-clip-finetuned
This model was trained from scratch on the soda-clip-loader dataset. It achieves the following results on the evaluation set:
- Loss: 1.9564
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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
4.6533 | 0.15 | 100 | 4.5663 |
4.5243 | 0.29 | 200 | 4.4131 |
4.2506 | 0.44 | 300 | 3.9908 |
3.9692 | 0.59 | 400 | 3.8105 |
3.7576 | 0.74 | 500 | 3.6515 |
3.5935 | 0.88 | 600 | 3.4758 |
3.3874 | 1.03 | 700 | 3.3259 |
3.1691 | 1.18 | 800 | 3.1645 |
3.021 | 1.33 | 900 | 3.0139 |
2.9045 | 1.47 | 1000 | 2.9027 |
2.8391 | 1.62 | 1100 | 2.8245 |
2.7293 | 1.77 | 1200 | 2.6703 |
2.6177 | 1.92 | 1300 | 2.5465 |
2.3473 | 2.06 | 1400 | 2.5076 |
2.1463 | 2.21 | 1500 | 2.4233 |
2.0842 | 2.36 | 1600 | 2.3488 |
2.0204 | 2.51 | 1700 | 2.2738 |
2.0013 | 2.65 | 1800 | 2.2473 |
1.9325 | 2.8 | 1900 | 2.2017 |
1.9072 | 2.95 | 2000 | 2.1397 |
1.5792 | 3.1 | 2100 | 2.1203 |
1.3949 | 3.24 | 2200 | 2.0973 |
1.3664 | 3.39 | 2300 | 2.0737 |
1.3545 | 3.54 | 2400 | 2.0320 |
1.3144 | 3.69 | 2500 | 2.0143 |
1.2897 | 3.83 | 2600 | 1.9552 |
1.2706 | 3.98 | 2700 | 1.9497 |
0.9014 | 4.13 | 2800 | 1.9983 |
0.8365 | 4.28 | 2900 | 1.9960 |
0.8187 | 4.42 | 3000 | 1.9886 |
0.8001 | 4.57 | 3100 | 1.9709 |
0.7979 | 4.72 | 3200 | 1.9513 |
0.7698 | 4.87 | 3300 | 1.9564 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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