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

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: 5.6776
- Accuracy: 0.4560
- F1: 0.4557

## 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: 11423
- 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  | 1.7114          | 0.4745   | 0.4746 |
| 0.5344        | 2.17  | 500  | 2.4454          | 0.4522   | 0.4441 |
| 0.5344        | 3.26  | 750  | 2.7492          | 0.4699   | 0.4693 |
| 0.2322        | 4.35  | 1000 | 3.0156          | 0.4336   | 0.4123 |
| 0.2322        | 5.43  | 1250 | 2.9947          | 0.4799   | 0.4819 |
| 0.1279        | 6.52  | 1500 | 3.7528          | 0.4506   | 0.4474 |
| 0.1279        | 7.61  | 1750 | 3.5806          | 0.4560   | 0.4560 |
| 0.0973        | 8.7   | 2000 | 3.8704          | 0.4545   | 0.4510 |
| 0.0973        | 9.78  | 2250 | 4.0113          | 0.4498   | 0.4450 |
| 0.0683        | 10.87 | 2500 | 3.5910          | 0.4676   | 0.4690 |
| 0.0683        | 11.96 | 2750 | 4.3665          | 0.4506   | 0.4480 |
| 0.0498        | 13.04 | 3000 | 4.2188          | 0.4799   | 0.4809 |
| 0.0498        | 14.13 | 3250 | 4.8550          | 0.4398   | 0.4315 |
| 0.0324        | 15.22 | 3500 | 4.7206          | 0.4630   | 0.4586 |
| 0.0324        | 16.3  | 3750 | 5.0101          | 0.4444   | 0.4392 |
| 0.025         | 17.39 | 4000 | 5.0926          | 0.4660   | 0.4667 |
| 0.025         | 18.48 | 4250 | 4.8167          | 0.4869   | 0.4886 |
| 0.0248        | 19.57 | 4500 | 5.1087          | 0.4606   | 0.4610 |
| 0.0248        | 20.65 | 4750 | 5.4661          | 0.4429   | 0.4365 |
| 0.0154        | 21.74 | 5000 | 5.2199          | 0.4730   | 0.4742 |
| 0.0154        | 22.83 | 5250 | 5.1442          | 0.4807   | 0.4825 |
| 0.0112        | 23.91 | 5500 | 5.4588          | 0.4691   | 0.4696 |
| 0.0112        | 25.0  | 5750 | 5.4026          | 0.4653   | 0.4654 |
| 0.0112        | 26.09 | 6000 | 5.6362          | 0.4506   | 0.4466 |
| 0.0112        | 27.17 | 6250 | 5.5405          | 0.4614   | 0.4620 |
| 0.0046        | 28.26 | 6500 | 5.6038          | 0.4591   | 0.4590 |
| 0.0046        | 29.35 | 6750 | 5.6776          | 0.4560   | 0.4557 |


### Framework versions

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