metadata

language:
  - en
base_model: gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - spearmanr
model-index:
  - name: hBERTv1_new_pretrain_w_init_48_ver2_stsb
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE STSB
          type: glue
          config: stsb
          split: validation
          args: stsb
        metrics:
          - name: Spearmanr
            type: spearmanr
            value: 0.12474663100095418

hBERTv1_new_pretrain_w_init_48_ver2_stsb

This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48 on the GLUE STSB dataset. It achieves the following results on the evaluation set:

Loss: 2.2509
Pearson: 0.1285
Spearmanr: 0.1247
Combined Score: 0.1266

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: 64
eval_batch_size: 64
seed: 10
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Pearson	Spearmanr	Combined Score
2.3716	1.0	90	2.4198	0.1235	0.0756	0.0995
2.1648	2.0	180	2.4218	0.0592	0.0606	0.0599
2.1915	3.0	270	2.5305	0.1143	0.0959	0.1051
2.1855	4.0	360	2.4912	0.1118	0.0969	0.1043
2.1858	5.0	450	2.3539	0.1130	0.1043	0.1087
2.1818	6.0	540	2.2509	0.1285	0.1247	0.1266
2.2562	7.0	630	2.3302	0.1043	0.0974	0.1009
2.2299	8.0	720	2.3749	0.1984	0.1422	0.1703
2.0676	9.0	810	2.3883	0.1300	0.1329	0.1314
1.926	10.0	900	2.5884	0.1259	0.1233	0.1246
1.7701	11.0	990	2.3776	0.1911	0.2059	0.1985

Framework versions

Transformers 4.34.0
Pytorch 1.14.0a0+410ce96
Datasets 2.14.5
Tokenizers 0.14.1