---
license: mit
base_model: haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-PO-CDF-CL-D2_data-cl-cardiff_cl_only44
  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_only44

This model is a fine-tuned version of [haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only](https://huggingface.co/haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 35.0455
- Accuracy: 0.4421
- F1: 0.4372

## 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: 44
- 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  | 22.7040         | 0.4236   | 0.4110 |
| 23.1676       | 2.17  | 500  | 21.6418         | 0.4336   | 0.4116 |
| 23.1676       | 3.26  | 750  | 24.6174         | 0.4267   | 0.4155 |
| 12.9705       | 4.35  | 1000 | 27.2959         | 0.4460   | 0.4447 |
| 12.9705       | 5.43  | 1250 | 28.1257         | 0.4375   | 0.4315 |
| 7.1171        | 6.52  | 1500 | 27.9161         | 0.4360   | 0.4279 |
| 7.1171        | 7.61  | 1750 | 29.9352         | 0.4383   | 0.4361 |
| 4.3718        | 8.7   | 2000 | 34.5593         | 0.4298   | 0.4191 |
| 4.3718        | 9.78  | 2250 | 34.0346         | 0.4421   | 0.4373 |
| 3.4048        | 10.87 | 2500 | 33.3230         | 0.4390   | 0.4351 |
| 3.4048        | 11.96 | 2750 | 35.1604         | 0.4367   | 0.4313 |
| 2.4739        | 13.04 | 3000 | 33.4441         | 0.4228   | 0.4170 |
| 2.4739        | 14.13 | 3250 | 32.9534         | 0.4367   | 0.4308 |
| 2.0055        | 15.22 | 3500 | 34.2647         | 0.4429   | 0.4414 |
| 2.0055        | 16.3  | 3750 | 33.4915         | 0.4460   | 0.4450 |
| 1.4812        | 17.39 | 4000 | 35.4776         | 0.4298   | 0.4249 |
| 1.4812        | 18.48 | 4250 | 35.4540         | 0.4375   | 0.4366 |
| 1.299         | 19.57 | 4500 | 34.2270         | 0.4468   | 0.4467 |
| 1.299         | 20.65 | 4750 | 34.7234         | 0.4460   | 0.4441 |
| 0.98          | 21.74 | 5000 | 34.8872         | 0.4352   | 0.4294 |
| 0.98          | 22.83 | 5250 | 34.8777         | 0.4383   | 0.4370 |
| 0.7847        | 23.91 | 5500 | 35.0968         | 0.4522   | 0.4518 |
| 0.7847        | 25.0  | 5750 | 34.3877         | 0.4329   | 0.4285 |
| 0.6835        | 26.09 | 6000 | 35.0458         | 0.4390   | 0.4365 |
| 0.6835        | 27.17 | 6250 | 35.2727         | 0.4360   | 0.4326 |
| 0.5378        | 28.26 | 6500 | 33.4029         | 0.4390   | 0.4353 |
| 0.5378        | 29.35 | 6750 | 35.0455         | 0.4421   | 0.4372 |


### Framework versions

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