metadata
tags:
- generated_from_trainer
datasets:
- Hartunka/processed_wikitext-103-raw-v1-rand-10
metrics:
- accuracy
model-index:
- name: distilbert_rand_10_v1
results:
- task:
name: Masked Language Modeling
type: fill-mask
dataset:
name: Hartunka/processed_wikitext-103-raw-v1-rand-10
type: Hartunka/processed_wikitext-103-raw-v1-rand-10
metrics:
- name: Accuracy
type: accuracy
value: 0.15367011357857263
distilbert_rand_10_v1
This model is a fine-tuned version of on the Hartunka/processed_wikitext-103-raw-v1-rand-10 dataset. It achieves the following results on the evaluation set:
- Loss: 8.4753
- Accuracy: 0.1537
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 8.3584 | 4.1982 | 10000 | 8.4600 | 0.1510 |
| 7.9814 | 8.3963 | 20000 | 8.6438 | 0.1520 |
| 7.1696 | 12.5945 | 30000 | 9.5950 | 0.1528 |
| 6.5265 | 16.7926 | 40000 | 10.7295 | 0.1521 |
| 6.2316 | 20.9908 | 50000 | 11.6464 | 0.1516 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.19.1