---
license: mit
base_model: haryoaw/scenario-TCR_data-en-cardiff_eng_only2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-PO-CDF-EN-FROM-EN-D2_data-en-cardiff_eng_only_beta-jason
  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_only_beta-jason

This model is a fine-tuned version of [haryoaw/scenario-TCR_data-en-cardiff_eng_only2](https://huggingface.co/haryoaw/scenario-TCR_data-en-cardiff_eng_only2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 26.5719
- Accuracy: 0.4056
- F1: 0.3992

## 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: 6666
- 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  | 21.2982         | 0.3690   | 0.3475 |
| No log        | 3.45  | 200  | 21.1284         | 0.3792   | 0.3741 |
| No log        | 5.17  | 300  | 21.4889         | 0.3893   | 0.3848 |
| No log        | 6.9   | 400  | 22.1337         | 0.3995   | 0.3933 |
| 21.5838       | 8.62  | 500  | 22.7814         | 0.4092   | 0.3879 |
| 21.5838       | 10.34 | 600  | 22.4046         | 0.3946   | 0.3846 |
| 21.5838       | 12.07 | 700  | 23.0168         | 0.4017   | 0.4022 |
| 21.5838       | 13.79 | 800  | 22.9590         | 0.3946   | 0.3914 |
| 21.5838       | 15.52 | 900  | 23.6863         | 0.3964   | 0.3942 |
| 15.9629       | 17.24 | 1000 | 24.4297         | 0.3977   | 0.3898 |
| 15.9629       | 18.97 | 1100 | 24.2709         | 0.3981   | 0.3931 |
| 15.9629       | 20.69 | 1200 | 24.9858         | 0.4123   | 0.4129 |
| 15.9629       | 22.41 | 1300 | 25.4483         | 0.4083   | 0.4062 |
| 15.9629       | 24.14 | 1400 | 26.0959         | 0.3942   | 0.3925 |
| 11.4549       | 25.86 | 1500 | 26.1345         | 0.4056   | 0.4041 |
| 11.4549       | 27.59 | 1600 | 26.4943         | 0.3871   | 0.3812 |
| 11.4549       | 29.31 | 1700 | 26.5719         | 0.4056   | 0.3992 |


### Framework versions

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