metadata

library_name: transformers
language:
  - en
base_model: gokulsrinivasagan/bert_base_lda_20_v1_book
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - spearmanr
model-index:
  - name: bert_base_lda_20_v1_book_stsb
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE STSB
          type: glue
          args: stsb
        metrics:
          - name: Spearmanr
            type: spearmanr
            value: 0.8381999392722225

bert_base_lda_20_v1_book_stsb

This model is a fine-tuned version of gokulsrinivasagan/bert_base_lda_20_v1_book on the GLUE STSB dataset. It achieves the following results on the evaluation set:

Loss: 0.6650
Pearson: 0.8407
Spearmanr: 0.8382
Combined Score: 0.8394

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
2.8738	1.0	23	2.4670	0.1765	0.1748	0.1756
1.4719	2.0	46	1.0280	0.7397	0.7404	0.7401
0.9801	3.0	69	0.8276	0.7956	0.7954	0.7955
0.783	4.0	92	0.7431	0.8197	0.8193	0.8195
0.5677	5.0	115	0.9075	0.8135	0.8152	0.8144
0.4407	6.0	138	0.7474	0.8267	0.8272	0.8269
0.3821	7.0	161	0.6753	0.8391	0.8371	0.8381
0.3036	8.0	184	0.8726	0.8246	0.8260	0.8253
0.269	9.0	207	0.7331	0.8311	0.8293	0.8302
0.2191	10.0	230	0.7562	0.8383	0.8368	0.8375
0.1854	11.0	253	0.7022	0.8365	0.8343	0.8354
0.1718	12.0	276	0.6650	0.8407	0.8382	0.8394
0.1685	13.0	299	0.7270	0.8350	0.8333	0.8342
0.1368	14.0	322	0.7532	0.8392	0.8376	0.8384
0.1351	15.0	345	0.8710	0.8379	0.8379	0.8379
0.1459	16.0	368	0.7801	0.8416	0.8398	0.8407
0.106	17.0	391	0.6833	0.8393	0.8380	0.8387

Framework versions

Transformers 4.46.3
Pytorch 2.2.1+cu118
Datasets 2.17.0
Tokenizers 0.20.3