---
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_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-CL-D2_data-cl-cardiff_cl_only_alpha-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: 16.1676
- Accuracy: 0.4005
- F1: 0.3988

## 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        | 1.09  | 250  | 11.7802         | 0.3727   | 0.3689 |
| 13.6353       | 2.17  | 500  | 10.9269         | 0.4120   | 0.4013 |
| 13.6353       | 3.26  | 750  | 10.7530         | 0.4066   | 0.4034 |
| 11.1498       | 4.35  | 1000 | 11.4698         | 0.4059   | 0.3994 |
| 11.1498       | 5.43  | 1250 | 11.1047         | 0.4182   | 0.4140 |
| 9.4007        | 6.52  | 1500 | 11.6114         | 0.4028   | 0.3911 |
| 9.4007        | 7.61  | 1750 | 12.1035         | 0.3935   | 0.3911 |
| 8.1024        | 8.7   | 2000 | 13.1654         | 0.4090   | 0.4035 |
| 8.1024        | 9.78  | 2250 | 12.8799         | 0.4020   | 0.4001 |
| 7.094         | 10.87 | 2500 | 12.5580         | 0.4082   | 0.3972 |
| 7.094         | 11.96 | 2750 | 12.7991         | 0.4228   | 0.4214 |
| 6.1021        | 13.04 | 3000 | 13.4827         | 0.3920   | 0.3906 |
| 6.1021        | 14.13 | 3250 | 14.8695         | 0.4159   | 0.4135 |
| 5.1725        | 15.22 | 3500 | 14.0881         | 0.4090   | 0.4081 |
| 5.1725        | 16.3  | 3750 | 14.4576         | 0.3866   | 0.3782 |
| 4.616         | 17.39 | 4000 | 14.4197         | 0.3819   | 0.3777 |
| 4.616         | 18.48 | 4250 | 15.2137         | 0.3997   | 0.3986 |
| 4.0484        | 19.57 | 4500 | 15.2744         | 0.3943   | 0.3939 |
| 4.0484        | 20.65 | 4750 | 15.3068         | 0.3858   | 0.3840 |
| 3.6271        | 21.74 | 5000 | 16.0691         | 0.4059   | 0.4030 |
| 3.6271        | 22.83 | 5250 | 15.7583         | 0.4120   | 0.4120 |
| 3.3297        | 23.91 | 5500 | 15.9934         | 0.4028   | 0.4002 |
| 3.3297        | 25.0  | 5750 | 16.3662         | 0.4097   | 0.4092 |
| 3.0762        | 26.09 | 6000 | 16.4914         | 0.4051   | 0.4040 |
| 3.0762        | 27.17 | 6250 | 16.4281         | 0.4051   | 0.4043 |
| 2.8363        | 28.26 | 6500 | 16.3025         | 0.4151   | 0.4149 |
| 2.8363        | 29.35 | 6750 | 16.1676         | 0.4005   | 0.3988 |


### Framework versions

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