metadata

library_name: transformers
language:
  - en
license: apache-2.0
base_model: google/bert_uncased_L-4_H-256_A-4
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - spearmanr
model-index:
  - name: bert_uncased_L-4_H-256_A-4_stsb
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE STSB
          type: glue
          args: stsb
        metrics:
          - name: Spearmanr
            type: spearmanr
            value: 0.8541619713648296

bert_uncased_L-4_H-256_A-4_stsb

This model is a fine-tuned version of google/bert_uncased_L-4_H-256_A-4 on the GLUE STSB dataset. It achieves the following results on the evaluation set:

Loss: 0.6283
Pearson: 0.8545
Spearmanr: 0.8542
Combined Score: 0.8543

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	Pearson	Spearmanr	Combined Score
5.5773	1.0	23	2.7412	0.3845	0.3343	0.3594
2.5793	2.0	46	1.9158	0.7727	0.7557	0.7642
1.5767	3.0	69	0.9541	0.7706	0.7473	0.7590
0.9474	4.0	92	0.7628	0.8133	0.8070	0.8101
0.7258	5.0	115	0.6785	0.8383	0.8429	0.8406
0.6162	6.0	138	0.6756	0.8436	0.8439	0.8437
0.5455	7.0	161	0.6391	0.8480	0.8504	0.8492
0.4912	8.0	184	0.6582	0.8461	0.8472	0.8466
0.4443	9.0	207	0.6561	0.8472	0.8482	0.8477
0.3995	10.0	230	0.6429	0.8504	0.8503	0.8503
0.3689	11.0	253	0.6283	0.8545	0.8542	0.8543
0.3418	12.0	276	0.6592	0.8520	0.8520	0.8520
0.3302	13.0	299	0.6507	0.8524	0.8530	0.8527
0.319	14.0	322	0.6484	0.8528	0.8526	0.8527
0.2863	15.0	345	0.6397	0.8526	0.8527	0.8526
0.2774	16.0	368	0.6379	0.8559	0.8555	0.8557

Framework versions

Transformers 4.46.3
Pytorch 2.2.1+cu118
Datasets 2.17.0
Tokenizers 0.20.3