distilroberta-base-finetuned-media-center
This model is a fine-tuned version of distilroberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3850
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 | 38 | 1.6960 |
No log | 2.0 | 76 | 1.5674 |
No log | 3.0 | 114 | 1.5541 |
No log | 4.0 | 152 | 1.5729 |
No log | 5.0 | 190 | 1.5164 |
No log | 6.0 | 228 | 1.5343 |
No log | 7.0 | 266 | 1.5232 |
No log | 8.0 | 304 | 1.4354 |
No log | 9.0 | 342 | 1.4203 |
No log | 10.0 | 380 | 1.3526 |
No log | 11.0 | 418 | 1.3911 |
No log | 12.0 | 456 | 1.4522 |
No log | 13.0 | 494 | 1.4324 |
1.4666 | 14.0 | 532 | 1.3606 |
1.4666 | 15.0 | 570 | 1.3669 |
1.4666 | 16.0 | 608 | 1.3420 |
1.4666 | 17.0 | 646 | 1.3544 |
1.4666 | 18.0 | 684 | 1.3346 |
1.4666 | 19.0 | 722 | 1.3747 |
1.4666 | 20.0 | 760 | 1.3850 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Downloads last month
- 8
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
๐
Ask for provider support
Model tree for Jorsini/distilroberta-base-finetuned-media-center
Base model
distilbert/distilroberta-base