metadata
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_tiny_lda_20_v1_book
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_tiny_lda_20_v1_book_mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.7132352941176471
- name: F1
type: f1
value: 0.8186046511627908
bert_tiny_lda_20_v1_book_mrpc
This model is a fine-tuned version of gokulsrinivasagan/bert_tiny_lda_20_v1_book on the GLUE MRPC dataset. It achieves the following results on the evaluation set:
- Loss: 0.5678
- Accuracy: 0.7132
- F1: 0.8186
- Combined Score: 0.7659
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 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 | F1 | Combined Score |
|---|---|---|---|---|---|---|
| 0.6236 | 1.0 | 15 | 0.5941 | 0.6936 | 0.8056 | 0.7496 |
| 0.5876 | 2.0 | 30 | 0.5767 | 0.7083 | 0.8194 | 0.7639 |
| 0.5497 | 3.0 | 45 | 0.5678 | 0.7132 | 0.8186 | 0.7659 |
| 0.503 | 4.0 | 60 | 0.5999 | 0.7157 | 0.8182 | 0.7669 |
| 0.4554 | 5.0 | 75 | 0.5997 | 0.7157 | 0.8193 | 0.7675 |
| 0.3873 | 6.0 | 90 | 0.6210 | 0.7034 | 0.7763 | 0.7399 |
| 0.3092 | 7.0 | 105 | 0.7192 | 0.7304 | 0.8308 | 0.7806 |
| 0.2575 | 8.0 | 120 | 0.7418 | 0.6593 | 0.7203 | 0.6898 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3