metadata
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_base_lda_5_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_base_lda_5_v1_mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.7107843137254902
- name: F1
type: f1
value: 0.8039867109634552
bert_base_lda_5_v1_mrpc
This model is a fine-tuned version of gokulsrinivasagan/bert_base_lda_5_v1 on the GLUE MRPC dataset. It achieves the following results on the evaluation set:
- Loss: 0.5821
- Accuracy: 0.7108
- F1: 0.8040
- Combined Score: 0.7574
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 |
|---|---|---|---|---|---|---|
| 0.6475 | 1.0 | 15 | 0.5919 | 0.6985 | 0.8099 | 0.7542 |
| 0.5596 | 2.0 | 30 | 0.5821 | 0.7108 | 0.8040 | 0.7574 |
| 0.4573 | 3.0 | 45 | 0.6319 | 0.6593 | 0.7549 | 0.7071 |
| 0.3282 | 4.0 | 60 | 0.8021 | 0.6299 | 0.7156 | 0.6728 |
| 0.1884 | 5.0 | 75 | 0.9919 | 0.6471 | 0.7517 | 0.6994 |
| 0.0919 | 6.0 | 90 | 1.1951 | 0.6740 | 0.7679 | 0.7210 |
| 0.0649 | 7.0 | 105 | 1.3058 | 0.6569 | 0.7595 | 0.7082 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3