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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
