---
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_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-CL-D2_data-cl-cardiff_cl_only_beta-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: 16.2119
- Accuracy: 0.3974
- F1: 0.3962

## 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        | 1.09  | 250  | 11.7960         | 0.3650   | 0.3427 |
| 13.5624       | 2.17  | 500  | 11.1810         | 0.3927   | 0.3922 |
| 13.5624       | 3.26  | 750  | 10.7353         | 0.3889   | 0.3725 |
| 11.0045       | 4.35  | 1000 | 11.0340         | 0.4113   | 0.4092 |
| 11.0045       | 5.43  | 1250 | 11.1511         | 0.3958   | 0.3764 |
| 9.4397        | 6.52  | 1500 | 11.3893         | 0.4128   | 0.4098 |
| 9.4397        | 7.61  | 1750 | 11.7867         | 0.4174   | 0.4136 |
| 8.0563        | 8.7   | 2000 | 12.7215         | 0.4020   | 0.3934 |
| 8.0563        | 9.78  | 2250 | 13.1991         | 0.4159   | 0.4158 |
| 7.071         | 10.87 | 2500 | 13.4791         | 0.3966   | 0.3938 |
| 7.071         | 11.96 | 2750 | 12.9321         | 0.4005   | 0.3939 |
| 5.9842        | 13.04 | 3000 | 13.5185         | 0.3873   | 0.3775 |
| 5.9842        | 14.13 | 3250 | 14.5623         | 0.4028   | 0.3984 |
| 5.0429        | 15.22 | 3500 | 14.7614         | 0.4012   | 0.3954 |
| 5.0429        | 16.3  | 3750 | 13.8500         | 0.4151   | 0.4149 |
| 4.4814        | 17.39 | 4000 | 14.0842         | 0.4051   | 0.4022 |
| 4.4814        | 18.48 | 4250 | 14.4055         | 0.3904   | 0.3804 |
| 4.0867        | 19.57 | 4500 | 15.5442         | 0.3858   | 0.3809 |
| 4.0867        | 20.65 | 4750 | 14.6236         | 0.3966   | 0.3951 |
| 3.5928        | 21.74 | 5000 | 14.9268         | 0.4005   | 0.3920 |
| 3.5928        | 22.83 | 5250 | 15.2065         | 0.3897   | 0.3884 |
| 3.2444        | 23.91 | 5500 | 16.5178         | 0.3889   | 0.3860 |
| 3.2444        | 25.0  | 5750 | 15.1592         | 0.3920   | 0.3879 |
| 3.0552        | 26.09 | 6000 | 15.4594         | 0.3974   | 0.3952 |
| 3.0552        | 27.17 | 6250 | 15.8492         | 0.3843   | 0.3842 |
| 2.8654        | 28.26 | 6500 | 15.8468         | 0.3827   | 0.3806 |
| 2.8654        | 29.35 | 6750 | 16.2119         | 0.3974   | 0.3962 |


### Framework versions

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