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

This model is a fine-tuned version of [haryoaw/scenario-TCR-data-glue-rte-model-bert-base-uncased](https://huggingface.co/haryoaw/scenario-TCR-data-glue-rte-model-bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6559
- Accuracy: 0.5848

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 78   | 2.2070          | 0.6101   |
| No log        | 2.0   | 156  | 2.3808          | 0.6282   |
| No log        | 3.0   | 234  | 2.7511          | 0.5921   |
| No log        | 4.0   | 312  | 2.9939          | 0.6209   |
| No log        | 5.0   | 390  | 2.8592          | 0.6426   |
| No log        | 6.0   | 468  | 2.8698          | 0.6390   |
| 1.4308        | 7.0   | 546  | 3.2244          | 0.6209   |
| 1.4308        | 8.0   | 624  | 2.9809          | 0.5848   |
| 1.4308        | 9.0   | 702  | 3.6688          | 0.6065   |
| 1.4308        | 10.0  | 780  | 3.6559          | 0.5848   |


### Framework versions

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