---
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_gamma-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_gamma-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: 16.7514
- Accuracy: 0.3977
- F1: 0.3868

## 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: 88458
- 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  | 12.6439         | 0.3228   | 0.2712 |
| No log        | 3.45  | 200  | 12.7249         | 0.3937   | 0.3882 |
| No log        | 5.17  | 300  | 12.8006         | 0.3902   | 0.3809 |
| No log        | 6.9   | 400  | 14.5097         | 0.3686   | 0.2952 |
| 12.7089       | 8.62  | 500  | 13.4001         | 0.4017   | 0.3928 |
| 12.7089       | 10.34 | 600  | 14.3419         | 0.4198   | 0.4042 |
| 12.7089       | 12.07 | 700  | 14.6078         | 0.3907   | 0.3741 |
| 12.7089       | 13.79 | 800  | 13.9429         | 0.3981   | 0.3942 |
| 12.7089       | 15.52 | 900  | 14.5756         | 0.3999   | 0.4000 |
| 8.5226        | 17.24 | 1000 | 14.8560         | 0.4012   | 0.3983 |
| 8.5226        | 18.97 | 1100 | 15.4018         | 0.4061   | 0.3972 |
| 8.5226        | 20.69 | 1200 | 15.6938         | 0.4127   | 0.4041 |
| 8.5226        | 22.41 | 1300 | 15.9840         | 0.4004   | 0.3879 |
| 8.5226        | 24.14 | 1400 | 15.9819         | 0.3977   | 0.3829 |
| 6.1231        | 25.86 | 1500 | 16.0163         | 0.4052   | 0.3938 |
| 6.1231        | 27.59 | 1600 | 16.2095         | 0.3968   | 0.3883 |
| 6.1231        | 29.31 | 1700 | 16.7514         | 0.3977   | 0.3868 |


### Framework versions

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