---
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-EN-FROM-CL-D2_data-en-cardiff_eng_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-EN-FROM-CL-D2_data-en-cardiff_eng_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: 15.6158
- Accuracy: 0.4061
- F1: 0.3950

## 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        | 1.72  | 100  | 12.5428         | 0.3796   | 0.3146 |
| No log        | 3.45  | 200  | 12.5657         | 0.3845   | 0.3414 |
| No log        | 5.17  | 300  | 12.6557         | 0.3911   | 0.3631 |
| No log        | 6.9   | 400  | 13.2594         | 0.4012   | 0.3807 |
| 13.0153       | 8.62  | 500  | 13.2352         | 0.3920   | 0.3836 |
| 13.0153       | 10.34 | 600  | 13.9522         | 0.3854   | 0.3638 |
| 13.0153       | 12.07 | 700  | 13.2917         | 0.3902   | 0.3891 |
| 13.0153       | 13.79 | 800  | 14.1281         | 0.3924   | 0.3931 |
| 13.0153       | 15.52 | 900  | 14.3501         | 0.4004   | 0.3889 |
| 9.1779        | 17.24 | 1000 | 14.2606         | 0.3955   | 0.3757 |
| 9.1779        | 18.97 | 1100 | 14.6113         | 0.4008   | 0.3953 |
| 9.1779        | 20.69 | 1200 | 14.9622         | 0.3973   | 0.3864 |
| 9.1779        | 22.41 | 1300 | 15.3755         | 0.3898   | 0.3652 |
| 9.1779        | 24.14 | 1400 | 15.1117         | 0.4087   | 0.4015 |
| 6.5007        | 25.86 | 1500 | 15.5084         | 0.4101   | 0.4075 |
| 6.5007        | 27.59 | 1600 | 15.5980         | 0.3955   | 0.3892 |
| 6.5007        | 29.31 | 1700 | 15.6158         | 0.4061   | 0.3950 |


### Framework versions

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