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---
library_name: transformers
tags:
- generated_from_trainer
datasets:
- gokulsrinivasagan/processed_wikitext-103-raw-v1-ld-5
metrics:
- accuracy
model-index:
- name: bert_tiny_lda_5_v1
results:
- task:
name: Masked Language Modeling
type: fill-mask
dataset:
name: gokulsrinivasagan/processed_wikitext-103-raw-v1-ld-5
type: gokulsrinivasagan/processed_wikitext-103-raw-v1-ld-5
metrics:
- name: Accuracy
type: accuracy
value: 0.16143611762379595
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert_tiny_lda_5_v1
This model is a fine-tuned version of [](https://huggingface.co/) on the gokulsrinivasagan/processed_wikitext-103-raw-v1-ld-5 dataset.
It achieves the following results on the evaluation set:
- Loss: 7.2608
- Accuracy: 0.1614
## 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: 160
- eval_batch_size: 160
- seed: 10
- optimizer: Use OptimizerNames.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 |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 7.735 | 6.9979 | 10000 | 7.6688 | 0.1533 |
| 7.3886 | 13.9958 | 20000 | 7.3523 | 0.1552 |
| 7.31 | 20.9937 | 30000 | 7.3179 | 0.1558 |
### Framework versions
- Transformers 4.46.1
- Pytorch 2.2.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.1
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