transformers pytorch safetensors bert generated_from_trainer base_model:haryoaw/scenario-TCR-data-glue-qnli-model-bert-base-uncased license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: haryoaw/scenario-TCR-data-glue-qnli-model-bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: scenario-KD-POST-DIV2-data-glue-qnli-model-haryoaw-scenario-TCR-data-glue-qnli-m
  results: []
---

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# scenario-KD-POST-DIV2-data-glue-qnli-model-haryoaw-scenario-TCR-data-glue-qnli-m

This model is a fine-tuned version of [haryoaw/scenario-TCR-data-glue-qnli-model-bert-base-uncased](https://huggingface.co/haryoaw/scenario-TCR-data-glue-qnli-model-bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5781
- Accuracy: 0.8658

## 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: 16
- eval_batch_size: 32
- seed: 45
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6969

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.708         | 1.0   | 3273  | 1.5714          | 0.8638   |
| 1.1033        | 2.0   | 6547  | 1.4824          | 0.8653   |
| 0.846         | 3.0   | 9820  | 1.6428          | 0.8602   |
| 0.7304        | 4.0   | 13094 | 1.5391          | 0.8656   |
| 0.662         | 5.0   | 16367 | 1.6077          | 0.8607   |
| 0.5835        | 6.0   | 19641 | 1.4562          | 0.8667   |
| 0.5322        | 7.0   | 22914 | 1.5354          | 0.8715   |
| 0.4772        | 8.0   | 26188 | 1.3541          | 0.8720   |
| 0.4584        | 9.0   | 29461 | 1.4711          | 0.8700   |
| 0.4448        | 10.0  | 32735 | 1.5773          | 0.8638   |
| 0.4137        | 11.0  | 36008 | 1.4558          | 0.8671   |
| 0.398         | 12.0  | 39282 | 1.4844          | 0.8695   |
| 0.3742        | 13.0  | 42555 | 1.5781          | 0.8658   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.16.0
- Tokenizers 0.15.0
