metadata

library_name: transformers
language:
  - en
base_model: gokulsrinivasagan/bert_base_lda_100_v1
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: bert_base_lda_100_v1_mrpc
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE MRPC
          type: glue
          args: mrpc
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.6838235294117647
          - name: F1
            type: f1
            value: 0.8122270742358079

bert_base_lda_100_v1_mrpc

This model is a fine-tuned version of gokulsrinivasagan/bert_base_lda_100_v1 on the GLUE MRPC dataset. It achieves the following results on the evaluation set:

Loss: 0.6229
Accuracy: 0.6838
F1: 0.8122
Combined Score: 0.7480

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: 0.001
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
1.6608	1.0	15	0.6274	0.6838	0.8122	0.7480
0.6437	2.0	30	0.6229	0.6838	0.8122	0.7480
0.6306	3.0	45	0.6274	0.6838	0.8122	0.7480
0.637	4.0	60	0.6244	0.6838	0.8122	0.7480
0.6341	5.0	75	0.6261	0.6838	0.8122	0.7480
0.6342	6.0	90	0.6254	0.6838	0.8122	0.7480
0.6328	7.0	105	0.6253	0.6838	0.8122	0.7480

Framework versions

Transformers 4.46.3
Pytorch 2.2.1+cu118
Datasets 2.17.0
Tokenizers 0.20.3