distilroberta-base-finetuned-media-left
This model is a fine-tuned version of distilroberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1486
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 1.0 | 146 | 1.6589 |
No log | 2.0 | 292 | 1.5801 |
No log | 3.0 | 438 | 1.5258 |
1.7336 | 4.0 | 584 | 1.4607 |
1.7336 | 5.0 | 730 | 1.4002 |
1.7336 | 6.0 | 876 | 1.4025 |
1.4357 | 7.0 | 1022 | 1.3493 |
1.4357 | 8.0 | 1168 | 1.3449 |
1.4357 | 9.0 | 1314 | 1.3117 |
1.4357 | 10.0 | 1460 | 1.2954 |
1.2491 | 11.0 | 1606 | 1.3056 |
1.2491 | 12.0 | 1752 | 1.2601 |
1.2491 | 13.0 | 1898 | 1.2488 |
1.1171 | 14.0 | 2044 | 1.2119 |
1.1171 | 15.0 | 2190 | 1.2133 |
1.1171 | 16.0 | 2336 | 1.1962 |
1.1171 | 17.0 | 2482 | 1.1902 |
1.0375 | 18.0 | 2628 | 1.1545 |
1.0375 | 19.0 | 2774 | 1.1702 |
1.0375 | 20.0 | 2920 | 1.1486 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for Jorsini/distilroberta-base-finetuned-media-left
Base model
distilbert/distilroberta-base