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

This model is a fine-tuned version of [haryoaw/scenario-TCR-data-glue-stsb-model-bert-base-uncased](https://huggingface.co/haryoaw/scenario-TCR-data-glue-stsb-model-bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8147
- Pearson: 0.8733
- Spearmanr: 0.8733

## 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 | Pearson | Spearmanr |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|
| No log        | 1.0   | 180  | 0.9770          | 0.8545  | 0.8536    |
| No log        | 2.0   | 360  | 0.9716          | 0.8515  | 0.8502    |
| 0.9627        | 3.0   | 540  | 0.9163          | 0.8605  | 0.8583    |
| 0.9627        | 4.0   | 720  | 0.8693          | 0.8697  | 0.8677    |
| 0.9627        | 5.0   | 900  | 0.8509          | 0.8644  | 0.8630    |
| 0.5217        | 6.0   | 1080 | 0.9000          | 0.8609  | 0.8614    |
| 0.5217        | 7.0   | 1260 | 0.8224          | 0.8699  | 0.8683    |
| 0.5217        | 8.0   | 1440 | 0.8331          | 0.8679  | 0.8669    |
| 0.4483        | 9.0   | 1620 | 0.8292          | 0.8688  | 0.8666    |
| 0.4483        | 10.0  | 1800 | 0.8816          | 0.8640  | 0.8651    |
| 0.4483        | 11.0  | 1980 | 0.8179          | 0.8747  | 0.8734    |
| 0.4135        | 12.0  | 2160 | 0.8333          | 0.8729  | 0.8724    |
| 0.4135        | 13.0  | 2340 | 0.7776          | 0.8755  | 0.8740    |
| 0.3879        | 14.0  | 2520 | 0.8050          | 0.8728  | 0.8708    |
| 0.3879        | 15.0  | 2700 | 0.7948          | 0.8759  | 0.8750    |
| 0.3879        | 16.0  | 2880 | 0.8190          | 0.8703  | 0.8684    |
| 0.3695        | 17.0  | 3060 | 0.8329          | 0.8684  | 0.8681    |
| 0.3695        | 18.0  | 3240 | 0.8943          | 0.8653  | 0.8673    |
| 0.3695        | 19.0  | 3420 | 0.8709          | 0.8703  | 0.8701    |
| 0.358         | 20.0  | 3600 | 0.8147          | 0.8733  | 0.8733    |


### Framework versions

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