distilbert_rand_50_v1
This model is a fine-tuned version of on the Hartunka/processed_wikitext-103-raw-v1-rand-50 dataset. It achieves the following results on the evaluation set:
- Loss: 10.1484
- Accuracy: 0.1523
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: 96
- eval_batch_size: 96
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 9.8834 | 4.1982 | 10000 | 10.1240 | 0.1515 |
| 9.0198 | 8.3963 | 20000 | 10.6225 | 0.1521 |
| 7.6604 | 12.5945 | 30000 | 11.9783 | 0.1538 |
| 6.7176 | 16.7926 | 40000 | 13.3879 | 0.1512 |
| 6.3921 | 20.9908 | 50000 | 14.1334 | 0.1518 |
Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
- Downloads last month
- 1
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Model tree for Hartunka/distilbert_rand_50_v1
Evaluation results
- Accuracy on Hartunka/processed_wikitext-103-raw-v1-rand-50self-reported0.152