metadata
library_name: transformers
tags:
- generated_from_trainer
datasets:
- Hartunka/processed_wikitext-103-raw-v1-rand-10
metrics:
- accuracy
model-index:
- name: bert_base_rand_10_v2
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: 0.15268124540882635
bert_base_rand_10_v2
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: 8.3559
- Accuracy: 0.1527
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 |
|---|---|---|---|---|
| 8.37 | 4.1982 | 10000 | 8.3540 | 0.1507 |
| 7.9402 | 8.3963 | 20000 | 8.5974 | 0.1519 |
| 7.1082 | 12.5945 | 30000 | 9.5775 | 0.1531 |
| 6.6025 | 16.7926 | 40000 | 10.4208 | 0.1519 |
| 6.2995 | 20.9908 | 50000 | 11.0614 | 0.1519 |
Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1