transformers pytorch bert generated_from_trainer base_model:haryoaw/scenario-TCR-data-glue-mnli-model-bert-base-uncased license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: haryoaw/scenario-TCR-data-glue-mnli-model-bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: scenario-KD-POST-DIV2-1000-data-glue-mnli-model-haryoaw-scenario-TCR-data-glue-m
  results: []
---

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# scenario-KD-POST-DIV2-1000-data-glue-mnli-model-haryoaw-scenario-TCR-data-glue-m

This model is a fine-tuned version of [haryoaw/scenario-TCR-data-glue-mnli-model-bert-base-uncased](https://huggingface.co/haryoaw/scenario-TCR-data-glue-mnli-model-bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9535
- Accuracy: 0.6863

## 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: 42
- 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 |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 0.3171        | 63.49  | 2000  | 2.8696          | 0.6878   |
| 0.2774        | 126.98 | 4000  | 2.8941          | 0.6898   |
| 0.261         | 190.48 | 6000  | 2.8202          | 0.6937   |
| 0.2503        | 253.97 | 8000  | 2.8936          | 0.6919   |
| 0.242         | 317.46 | 10000 | 2.8649          | 0.6921   |
| 0.2368        | 380.95 | 12000 | 2.8884          | 0.6960   |
| 0.2313        | 444.44 | 14000 | 2.8741          | 0.6944   |
| 0.2279        | 507.94 | 16000 | 2.8976          | 0.6923   |
| 0.2252        | 571.43 | 18000 | 2.8704          | 0.6918   |
| 0.222         | 634.92 | 20000 | 3.0028          | 0.6943   |
| 0.2211        | 698.41 | 22000 | 2.9535          | 0.6863   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.1.1
- Datasets 2.14.5
- Tokenizers 0.13.3
