---
license: mit
base_model: haryoaw/scenario-TCR_data-cl-cardiff_cl_only2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-PO-CDF-CL-D2_data-cl-cardiff_cl_only_gamma-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-CL-D2_data-cl-cardiff_cl_only_gamma-jason

This model is a fine-tuned version of [haryoaw/scenario-TCR_data-cl-cardiff_cl_only2](https://huggingface.co/haryoaw/scenario-TCR_data-cl-cardiff_cl_only2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 17.5985
- Accuracy: 0.3958
- F1: 0.3956

## 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: 88458
- 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        | 1.09  | 250  | 11.6483         | 0.3650   | 0.3609 |
| 13.703        | 2.17  | 500  | 11.1328         | 0.3843   | 0.3821 |
| 13.703        | 3.26  | 750  | 10.9310         | 0.3997   | 0.3991 |
| 11.1159       | 4.35  | 1000 | 11.8248         | 0.4035   | 0.3976 |
| 11.1159       | 5.43  | 1250 | 11.2452         | 0.4074   | 0.4047 |
| 9.5324        | 6.52  | 1500 | 12.0093         | 0.4082   | 0.4079 |
| 9.5324        | 7.61  | 1750 | 12.4283         | 0.4043   | 0.4042 |
| 8.2184        | 8.7   | 2000 | 12.1651         | 0.3897   | 0.3860 |
| 8.2184        | 9.78  | 2250 | 13.2395         | 0.4012   | 0.4006 |
| 7.0214        | 10.87 | 2500 | 13.4757         | 0.4028   | 0.4030 |
| 7.0214        | 11.96 | 2750 | 14.5726         | 0.3943   | 0.3878 |
| 6.0532        | 13.04 | 3000 | 15.9024         | 0.3966   | 0.3918 |
| 6.0532        | 14.13 | 3250 | 16.2467         | 0.3819   | 0.3672 |
| 5.3338        | 15.22 | 3500 | 14.5700         | 0.3912   | 0.3911 |
| 5.3338        | 16.3  | 3750 | 14.7870         | 0.3989   | 0.3969 |
| 4.7168        | 17.39 | 4000 | 16.6837         | 0.3804   | 0.3758 |
| 4.7168        | 18.48 | 4250 | 16.3479         | 0.3835   | 0.3807 |
| 4.052         | 19.57 | 4500 | 16.3096         | 0.3897   | 0.3860 |
| 4.052         | 20.65 | 4750 | 16.4666         | 0.3958   | 0.3947 |
| 3.6691        | 21.74 | 5000 | 16.7052         | 0.3935   | 0.3851 |
| 3.6691        | 22.83 | 5250 | 16.9439         | 0.4012   | 0.3985 |
| 3.3107        | 23.91 | 5500 | 16.8777         | 0.4051   | 0.4025 |
| 3.3107        | 25.0  | 5750 | 17.4662         | 0.3897   | 0.3866 |
| 2.9893        | 26.09 | 6000 | 17.5858         | 0.3951   | 0.3939 |
| 2.9893        | 27.17 | 6250 | 17.6884         | 0.3935   | 0.3928 |
| 2.8471        | 28.26 | 6500 | 17.7042         | 0.3881   | 0.3871 |
| 2.8471        | 29.35 | 6750 | 17.5985         | 0.3958   | 0.3956 |


### Framework versions

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