---
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_alpha-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_alpha-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: 25.9311
- Accuracy: 0.4056
- F1: 0.3983

## 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: 2222
- 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  | 21.3190         | 0.3576   | 0.3272 |
| No log        | 3.45  | 200  | 21.9669         | 0.3765   | 0.3322 |
| No log        | 5.17  | 300  | 21.3943         | 0.3880   | 0.3770 |
| No log        | 6.9   | 400  | 22.4346         | 0.3937   | 0.3679 |
| 21.6763       | 8.62  | 500  | 22.0732         | 0.3898   | 0.3832 |
| 21.6763       | 10.34 | 600  | 22.3971         | 0.3915   | 0.3870 |
| 21.6763       | 12.07 | 700  | 22.5065         | 0.3946   | 0.3879 |
| 21.6763       | 13.79 | 800  | 22.9460         | 0.3942   | 0.3906 |
| 21.6763       | 15.52 | 900  | 22.6589         | 0.4123   | 0.4073 |
| 15.4435       | 17.24 | 1000 | 23.3626         | 0.4039   | 0.3969 |
| 15.4435       | 18.97 | 1100 | 23.8309         | 0.3990   | 0.3925 |
| 15.4435       | 20.69 | 1200 | 24.5910         | 0.3955   | 0.3914 |
| 15.4435       | 22.41 | 1300 | 24.9435         | 0.3893   | 0.3778 |
| 15.4435       | 24.14 | 1400 | 25.2576         | 0.3920   | 0.3836 |
| 11.044        | 25.86 | 1500 | 25.6593         | 0.3951   | 0.3861 |
| 11.044        | 27.59 | 1600 | 25.6976         | 0.3973   | 0.3902 |
| 11.044        | 29.31 | 1700 | 25.9311         | 0.4056   | 0.3983 |


### Framework versions

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