---
license: mit
base_model: haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-PO-CDF-EN-FROM-EN-D2_data-en-cardiff_eng_only55
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# scenario-KD-PO-CDF-EN-FROM-EN-D2_data-en-cardiff_eng_only55

This model is a fine-tuned version of [haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only](https://huggingface.co/haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 23.6899
- Accuracy: 0.4665
- F1: 0.4662

## 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: 55
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.72  | 100  | 15.5667         | 0.4356   | 0.4288 |
| No log        | 3.45  | 200  | 17.1164         | 0.4418   | 0.4096 |
| No log        | 5.17  | 300  | 18.8679         | 0.4634   | 0.4606 |
| No log        | 6.9   | 400  | 19.9135         | 0.4550   | 0.4494 |
| 9.9963        | 8.62  | 500  | 23.0517         | 0.4581   | 0.4517 |
| 9.9963        | 10.34 | 600  | 21.4184         | 0.4493   | 0.4394 |
| 9.9963        | 12.07 | 700  | 22.8898         | 0.4621   | 0.4584 |
| 9.9963        | 13.79 | 800  | 22.6673         | 0.4462   | 0.4352 |
| 9.9963        | 15.52 | 900  | 23.8054         | 0.4616   | 0.4605 |
| 1.7937        | 17.24 | 1000 | 23.0995         | 0.4586   | 0.4524 |
| 1.7937        | 18.97 | 1100 | 23.2337         | 0.4709   | 0.4682 |
| 1.7937        | 20.69 | 1200 | 24.9664         | 0.4669   | 0.4646 |
| 1.7937        | 22.41 | 1300 | 23.8143         | 0.4700   | 0.4695 |
| 1.7937        | 24.14 | 1400 | 23.9374         | 0.4581   | 0.4546 |
| 0.6046        | 25.86 | 1500 | 24.0218         | 0.4647   | 0.4651 |
| 0.6046        | 27.59 | 1600 | 23.0812         | 0.4740   | 0.4735 |
| 0.6046        | 29.31 | 1700 | 23.6899         | 0.4665   | 0.4662 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3