---
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_beta-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_beta-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: 16.2943
- Accuracy: 0.4026
- F1: 0.3951

## 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: 6666
- 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  | 12.5546         | 0.3884   | 0.3802 |
| No log        | 3.45  | 200  | 12.5713         | 0.3889   | 0.3881 |
| No log        | 5.17  | 300  | 12.7463         | 0.4017   | 0.3840 |
| No log        | 6.9   | 400  | 13.0469         | 0.3884   | 0.3865 |
| 12.7004       | 8.62  | 500  | 13.4306         | 0.3964   | 0.3948 |
| 12.7004       | 10.34 | 600  | 13.5764         | 0.3964   | 0.3952 |
| 12.7004       | 12.07 | 700  | 13.8288         | 0.4074   | 0.4072 |
| 12.7004       | 13.79 | 800  | 14.3994         | 0.3955   | 0.3835 |
| 12.7004       | 15.52 | 900  | 14.4145         | 0.4171   | 0.4126 |
| 8.7663        | 17.24 | 1000 | 14.7236         | 0.4039   | 0.3966 |
| 8.7663        | 18.97 | 1100 | 15.3258         | 0.3920   | 0.3750 |
| 8.7663        | 20.69 | 1200 | 15.4501         | 0.3973   | 0.3945 |
| 8.7663        | 22.41 | 1300 | 15.6468         | 0.4026   | 0.3945 |
| 8.7663        | 24.14 | 1400 | 15.8710         | 0.4096   | 0.4019 |
| 6.1643        | 25.86 | 1500 | 15.9974         | 0.4136   | 0.4077 |
| 6.1643        | 27.59 | 1600 | 16.6029         | 0.3840   | 0.3721 |
| 6.1643        | 29.31 | 1700 | 16.2943         | 0.4026   | 0.3951 |


### Framework versions

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