| --- |
| language: |
| - en |
| base_model: Hartunka/tiny_bert_rand_100_v1 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - glue |
| metrics: |
| - accuracy |
| model-index: |
| - name: tiny_bert_rand_100_v1_mnli |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: GLUE MNLI |
| type: glue |
| args: mnli |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.620626525630594 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # tiny_bert_rand_100_v1_mnli |
| |
| This model is a fine-tuned version of [Hartunka/tiny_bert_rand_100_v1](https://huggingface.co/Hartunka/tiny_bert_rand_100_v1) on the GLUE MNLI dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8518 |
| - Accuracy: 0.6206 |
| |
| ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 50 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 0.9939 | 1.0 | 1534 | 0.9340 | 0.5477 | |
| | 0.9106 | 2.0 | 3068 | 0.8888 | 0.5792 | |
| | 0.8576 | 3.0 | 4602 | 0.8594 | 0.6055 | |
| | 0.8116 | 4.0 | 6136 | 0.8516 | 0.6134 | |
| | 0.7679 | 5.0 | 7670 | 0.8467 | 0.6204 | |
| | 0.7263 | 6.0 | 9204 | 0.8595 | 0.6275 | |
| | 0.6861 | 7.0 | 10738 | 0.8681 | 0.6259 | |
| | 0.6464 | 8.0 | 12272 | 0.9058 | 0.6231 | |
| | 0.6076 | 9.0 | 13806 | 0.9309 | 0.6247 | |
| | 0.5699 | 10.0 | 15340 | 0.9937 | 0.6231 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.40.0 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.5.0 |
| - Tokenizers 0.19.1 |
| |
