metadata

library_name: transformers
language:
  - en
license: apache-2.0
base_model: google/bert_uncased_L-4_H-512_A-8
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - spearmanr
model-index:
  - name: bert_uncased_L-4_H-512_A-8_stsb
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE STSB
          type: glue
          args: stsb
        metrics:
          - name: Spearmanr
            type: spearmanr
            value: 0.8704339623572931

bert_uncased_L-4_H-512_A-8_stsb

This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the GLUE STSB dataset. It achieves the following results on the evaluation set:

Loss: 0.5646
Pearson: 0.8739
Spearmanr: 0.8704
Combined Score: 0.8721

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
2.5878	1.0	23	0.9754	0.7823	0.7580	0.7702
0.797	2.0	46	0.7766	0.8466	0.8482	0.8474
0.5786	3.0	69	0.6314	0.8603	0.8587	0.8595
0.4961	4.0	92	0.6342	0.8643	0.8637	0.8640
0.3944	5.0	115	0.6018	0.8694	0.8683	0.8689
0.3362	6.0	138	0.6101	0.8659	0.8657	0.8658
0.2932	7.0	161	0.6056	0.8678	0.8666	0.8672
0.2495	8.0	184	0.6255	0.8679	0.8672	0.8675
0.2268	9.0	207	0.5970	0.8699	0.8685	0.8692
0.2037	10.0	230	0.6517	0.8691	0.8672	0.8682
0.191	11.0	253	0.6017	0.8709	0.8677	0.8693
0.1678	12.0	276	0.6097	0.8704	0.8685	0.8695
0.1546	13.0	299	0.6052	0.8713	0.8701	0.8707
0.1486	14.0	322	0.5914	0.8714	0.8689	0.8701
0.1372	15.0	345	0.6175	0.8738	0.8702	0.8720
0.131	16.0	368	0.5826	0.8727	0.8702	0.8715
0.1216	17.0	391	0.5779	0.8717	0.8686	0.8702
0.1145	18.0	414	0.5646	0.8739	0.8704	0.8721
0.1158	19.0	437	0.5811	0.8738	0.8711	0.8724
0.109	20.0	460	0.5896	0.8763	0.8720	0.8742
0.105	21.0	483	0.5863	0.8737	0.8705	0.8721
0.0995	22.0	506	0.5758	0.8741	0.8701	0.8721
0.0971	23.0	529	0.5781	0.8748	0.8713	0.8731

Framework versions

Transformers 4.46.3
Pytorch 2.2.1+cu118
Datasets 2.17.0
Tokenizers 0.20.3