metadata

language:
  - en
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: hBERTv2_new_pretrain_48_emb_com_mrpc
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE MRPC
          type: glue
          config: mrpc
          split: validation
          args: mrpc
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7107843137254902
          - name: F1
            type: f1
            value: 0.8115015974440896

hBERTv2_new_pretrain_48_emb_com_mrpc

This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new_emb_compress_48 on the GLUE MRPC dataset. It achieves the following results on the evaluation set:

Loss: 0.5857
Accuracy: 0.7108
F1: 0.8115
Combined Score: 0.7611

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: 4e-05
train_batch_size: 128
eval_batch_size: 128
seed: 10
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Combined Score
0.6593	1.0	29	0.6031	0.6789	0.7863	0.7326
0.6335	2.0	58	0.6834	0.6275	0.7043	0.6659
0.5907	3.0	87	0.5857	0.7108	0.8115	0.7611
0.5875	4.0	116	0.6222	0.6495	0.7223	0.6859
0.5292	5.0	145	0.6143	0.6838	0.7854	0.7346
0.4529	6.0	174	0.7419	0.6299	0.7135	0.6717
0.3827	7.0	203	0.7416	0.6593	0.7513	0.7053
0.3061	8.0	232	0.8274	0.6593	0.7574	0.7084

Framework versions

Transformers 4.30.2
Pytorch 1.14.0a0+410ce96
Datasets 2.12.0
Tokenizers 0.13.3