metadata
tags:
- generated_from_trainer
datasets:
- Hartunka/processed_wikitext-103-raw-v1-rand-100_v2
metrics:
- accuracy
model-index:
- name: tiny_bert_rand_100_v2
results:
- task:
name: Masked Language Modeling
type: fill-mask
dataset:
name: Hartunka/processed_wikitext-103-raw-v1-rand-100_v2
type: Hartunka/processed_wikitext-103-raw-v1-rand-100_v2
metrics:
- name: Accuracy
type: accuracy
value: 0.15234220489348477
tiny_bert_rand_100_v2
This model is a fine-tuned version of on the Hartunka/processed_wikitext-103-raw-v1-rand-100_v2 dataset. It achieves the following results on the evaluation set:
- Loss: 10.8907
- 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: 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 |
|---|---|---|---|---|
| 10.6784 | 4.1982 | 10000 | 10.8779 | 0.1501 |
| 10.0232 | 8.3963 | 20000 | 11.1558 | 0.1530 |
| 9.1752 | 12.5945 | 30000 | 11.7162 | 0.1537 |
| 8.2175 | 16.7926 | 40000 | 12.6584 | 0.1513 |
| 7.4989 | 20.9908 | 50000 | 13.4746 | 0.1518 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.19.1