metadata
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/distilbert_lda_100_v1_book
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: distilbert_lda_100_v1_book_qnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QNLI
type: glue
args: qnli
metrics:
- name: Accuracy
type: accuracy
value: 0.8482518762584661
distilbert_lda_100_v1_book_qnli
This model is a fine-tuned version of gokulsrinivasagan/distilbert_lda_100_v1_book on the GLUE QNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.3533
- Accuracy: 0.8483
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: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- 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
- num_epochs: 50
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.4749 | 1.0 | 410 | 0.3737 | 0.8298 |
0.3589 | 2.0 | 820 | 0.3533 | 0.8483 |
0.2756 | 3.0 | 1230 | 0.3595 | 0.8506 |
0.201 | 4.0 | 1640 | 0.4855 | 0.8340 |
0.1427 | 5.0 | 2050 | 0.4893 | 0.8459 |
0.1037 | 6.0 | 2460 | 0.5452 | 0.8494 |
0.0773 | 7.0 | 2870 | 0.6410 | 0.8451 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.2.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.1