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# scenario-TCR-data-glue-qnli-model-bert-base-uncased

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4691
- Accuracy: 0.8885

## 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: 8
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.303         | 1.0   | 3273  | 0.2478          | 0.9023   |
| 0.2095        | 2.0   | 6546  | 0.2681          | 0.9033   |
| 0.1365        | 3.0   | 9819  | 0.3354          | 0.8993   |
| 0.1107        | 4.0   | 13093 | 0.3548          | 0.8971   |
| 0.0963        | 5.0   | 16366 | 0.4401          | 0.8922   |
| 0.0862        | 6.0   | 19639 | 0.4351          | 0.8876   |
| 0.0818        | 7.0   | 22912 | 0.4691          | 0.8885   |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "scenario-TCR-data-glue-qnli-model-bert-base-uncased", "results": []}]}
transformers safetensors bert text-classification generated_from_trainer base_model:bert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us