transformers safetensors bert generated_from_trainer base_model:haryoaw/scenario-TCR-data-glue-mrpc-model-bert-base-uncased license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: haryoaw/scenario-TCR-data-glue-mrpc-model-bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-POST-DIV2-data-glue-mrpc-model-haryoaw-scenario-TCR-data-glue-mrpc-m
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# scenario-KD-POST-DIV2-data-glue-mrpc-model-haryoaw-scenario-TCR-data-glue-mrpc-m

This model is a fine-tuned version of [haryoaw/scenario-TCR-data-glue-mrpc-model-bert-base-uncased](https://huggingface.co/haryoaw/scenario-TCR-data-glue-mrpc-model-bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 7.0133
- Accuracy: 0.8039
- F1: 0.8738

## 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: 32
- eval_batch_size: 32
- seed: 45
- 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 115  | 7.0251          | 0.7647   | 0.8154 |
| No log        | 2.0   | 230  | 5.7580          | 0.7843   | 0.8514 |
| No log        | 3.0   | 345  | 7.4938          | 0.7770   | 0.8286 |
| No log        | 4.0   | 460  | 6.2189          | 0.7843   | 0.8576 |
| 3.6918        | 5.0   | 575  | 5.8885          | 0.7990   | 0.8561 |
| 3.6918        | 6.0   | 690  | 6.4826          | 0.8064   | 0.8707 |
| 3.6918        | 7.0   | 805  | 4.2142          | 0.8358   | 0.8847 |
| 3.6918        | 8.0   | 920  | 5.9997          | 0.8137   | 0.8643 |
| 0.8883        | 9.0   | 1035 | 5.8321          | 0.8137   | 0.8671 |
| 0.8883        | 10.0  | 1150 | 7.0043          | 0.8113   | 0.8623 |
| 0.8883        | 11.0  | 1265 | 6.6340          | 0.8137   | 0.8703 |
| 0.8883        | 12.0  | 1380 | 7.0133          | 0.8039   | 0.8738 |


### Framework versions

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