tinybert_base_train_kd_sst2
This model is a fine-tuned version of gokulsrinivasagan/tinybert_base_train_kd on the GLUE SST2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4014
- Accuracy: 0.8337
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 | Accuracy |
|---|---|---|---|---|
| 0.3628 | 1.0 | 264 | 0.4199 | 0.8291 |
| 0.2393 | 2.0 | 528 | 0.4014 | 0.8337 |
| 0.179 | 3.0 | 792 | 0.4737 | 0.8177 |
| 0.1433 | 4.0 | 1056 | 0.4492 | 0.8349 |
| 0.1139 | 5.0 | 1320 | 0.4927 | 0.8326 |
| 0.0936 | 6.0 | 1584 | 0.4424 | 0.8532 |
| 0.0778 | 7.0 | 1848 | 0.5840 | 0.8349 |
Framework versions
- Transformers 4.51.2
- Pytorch 2.6.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1
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Model tree for gokulsrinivasagan/tinybert_base_train_kd_sst2
Base model
distilbert/distilbert-base-uncased
Finetuned
gokulsrinivasagan/tinybert_base_train_kd Dataset used to train gokulsrinivasagan/tinybert_base_train_kd_sst2
Evaluation results
- Accuracy on GLUE SST2self-reported0.834