README.md

metadata

library_name: transformers
language:
  - en
license: apache-2.0
base_model: gokulsrinivasagan/tinybert_base_train_kd
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - spearmanr
model-index:
  - name: tinybert_base_train_kd_stsb
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE STSB
          type: glue
          args: stsb
        metrics:
          - name: Spearmanr
            type: spearmanr
            value: 0.8229059501737404

tinybert_base_train_kd_stsb

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

• Loss: 0.7127
• Pearson: 0.8275
• Spearmanr: 0.8229
• Combined Score: 0.8252

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
2.613	1.0	23	2.5624	0.1145	0.1287	0.1216
1.8186	2.0	46	1.1171	0.7169	0.7142	0.7155
1.1222	3.0	69	1.0925	0.7803	0.7822	0.7813
0.8374	4.0	92	0.7486	0.8170	0.8122	0.8146
0.7145	5.0	115	0.7349	0.8232	0.8204	0.8218
0.5299	6.0	138	0.7158	0.8318	0.8265	0.8292
0.4359	7.0	161	0.7249	0.8288	0.8267	0.8278
0.3798	8.0	184	0.7129	0.8281	0.8235	0.8258
0.3253	9.0	207	0.7902	0.8171	0.8150	0.8161
0.277	10.0	230	0.7336	0.8229	0.8195	0.8212
0.255	11.0	253	0.7127	0.8275	0.8229	0.8252
0.2257	12.0	276	0.7646	0.8233	0.8216	0.8225
0.204	13.0	299	0.8714	0.8245	0.8235	0.8240
0.1957	14.0	322	0.7891	0.8213	0.8179	0.8196
0.1725	15.0	345	0.7348	0.8230	0.8193	0.8212
0.1621	16.0	368	0.7909	0.8179	0.8149	0.8164

Framework versions

• Transformers 4.51.2
• Pytorch 2.6.0+cu126
• Datasets 3.5.0
• Tokenizers 0.21.1