---
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_delta-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_delta-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: 26.0242
- Accuracy: 0.3907
- F1: 0.3859

## 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: 7777
- 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  | 21.4135         | 0.3382   | 0.1963 |
| No log        | 3.45  | 200  | 21.5272         | 0.3845   | 0.3506 |
| No log        | 5.17  | 300  | 22.3621         | 0.3748   | 0.3274 |
| No log        | 6.9   | 400  | 21.4286         | 0.3959   | 0.3950 |
| 21.7005       | 8.62  | 500  | 22.3157         | 0.3937   | 0.3766 |
| 21.7005       | 10.34 | 600  | 22.4956         | 0.4065   | 0.4025 |
| 21.7005       | 12.07 | 700  | 22.5078         | 0.4070   | 0.4061 |
| 21.7005       | 13.79 | 800  | 23.7347         | 0.4017   | 0.3816 |
| 21.7005       | 15.52 | 900  | 23.6096         | 0.3964   | 0.3828 |
| 15.6576       | 17.24 | 1000 | 24.2553         | 0.3836   | 0.3594 |
| 15.6576       | 18.97 | 1100 | 24.5136         | 0.3876   | 0.3805 |
| 15.6576       | 20.69 | 1200 | 24.4989         | 0.3986   | 0.3963 |
| 15.6576       | 22.41 | 1300 | 24.8175         | 0.4149   | 0.4117 |
| 15.6576       | 24.14 | 1400 | 25.9234         | 0.4008   | 0.3884 |
| 11.4297       | 25.86 | 1500 | 25.3551         | 0.4026   | 0.3979 |
| 11.4297       | 27.59 | 1600 | 25.9706         | 0.3995   | 0.3952 |
| 11.4297       | 29.31 | 1700 | 26.0242         | 0.3907   | 0.3859 |


### Framework versions

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