metadata
tags:
- generated_from_trainer
datasets:
- Hartunka/processed_wikitext-103-raw-v1-km-5_v2
metrics:
- accuracy
model-index:
- name: tiny_bert_km_5_v2
results:
- task:
name: Masked Language Modeling
type: fill-mask
dataset:
name: Hartunka/processed_wikitext-103-raw-v1-km-5_v2
type: Hartunka/processed_wikitext-103-raw-v1-km-5_v2
metrics:
- name: Accuracy
type: accuracy
value: 0.2284850539639487
tiny_bert_km_5_v2
This model is a fine-tuned version of on the Hartunka/processed_wikitext-103-raw-v1-km-5_v2 dataset. It achieves the following results on the evaluation set:
- Loss: 5.4958
- Accuracy: 0.2285
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 |
|---|---|---|---|---|
| 6.435 | 4.1982 | 10000 | 6.3815 | 0.1489 |
| 6.1783 | 8.3963 | 20000 | 6.3055 | 0.1532 |
| 6.0524 | 12.5945 | 30000 | 6.2819 | 0.1547 |
| 5.7467 | 16.7926 | 40000 | 5.9122 | 0.1815 |
| 5.4323 | 20.9908 | 50000 | 5.5983 | 0.2250 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.19.1