---
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_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-CL-D2_data-cl-cardiff_cl_only_delta-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: 15.4781
- Accuracy: 0.4043
- F1: 0.3989

## 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        | 1.09  | 250  | 11.8950         | 0.3735   | 0.3391 |
| 13.6959       | 2.17  | 500  | 11.1790         | 0.3850   | 0.3767 |
| 13.6959       | 3.26  | 750  | 11.1554         | 0.4082   | 0.4075 |
| 11.138        | 4.35  | 1000 | 11.3070         | 0.4090   | 0.4082 |
| 11.138        | 5.43  | 1250 | 11.4384         | 0.4043   | 0.4029 |
| 9.5889        | 6.52  | 1500 | 11.3483         | 0.4090   | 0.4061 |
| 9.5889        | 7.61  | 1750 | 12.4116         | 0.4020   | 0.3985 |
| 8.2638        | 8.7   | 2000 | 11.7820         | 0.3997   | 0.3798 |
| 8.2638        | 9.78  | 2250 | 11.9709         | 0.4012   | 0.4001 |
| 6.9206        | 10.87 | 2500 | 12.7419         | 0.4198   | 0.4197 |
| 6.9206        | 11.96 | 2750 | 13.1813         | 0.4074   | 0.4078 |
| 5.993         | 13.04 | 3000 | 13.5405         | 0.4074   | 0.4062 |
| 5.993         | 14.13 | 3250 | 13.6698         | 0.3920   | 0.3860 |
| 5.1998        | 15.22 | 3500 | 13.8872         | 0.3989   | 0.3991 |
| 5.1998        | 16.3  | 3750 | 13.8954         | 0.4074   | 0.4076 |
| 4.6117        | 17.39 | 4000 | 14.2214         | 0.4090   | 0.4090 |
| 4.6117        | 18.48 | 4250 | 13.7015         | 0.4097   | 0.4033 |
| 4.0848        | 19.57 | 4500 | 14.8333         | 0.3912   | 0.3798 |
| 4.0848        | 20.65 | 4750 | 14.0279         | 0.4035   | 0.3989 |
| 3.7518        | 21.74 | 5000 | 14.6064         | 0.4035   | 0.4024 |
| 3.7518        | 22.83 | 5250 | 14.6257         | 0.3943   | 0.3914 |
| 3.285         | 23.91 | 5500 | 14.5868         | 0.4020   | 0.3968 |
| 3.285         | 25.0  | 5750 | 15.5230         | 0.3843   | 0.3756 |
| 3.0056        | 26.09 | 6000 | 14.9209         | 0.3904   | 0.3811 |
| 3.0056        | 27.17 | 6250 | 14.9466         | 0.3981   | 0.3968 |
| 2.8364        | 28.26 | 6500 | 15.5711         | 0.3881   | 0.3824 |
| 2.8364        | 29.35 | 6750 | 15.4781         | 0.4043   | 0.3989 |


### Framework versions

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