---
license: mit
base_model: haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-PO-CDF-EN-FROM-EN-D2_data-en-cardiff_eng_only66
  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-EN-D2_data-en-cardiff_eng_only66

This model is a fine-tuned version of [haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only](https://huggingface.co/haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 24.7382
- Accuracy: 0.4550
- F1: 0.4534

## 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: 66
- 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  | 15.4704         | 0.4568   | 0.4535 |
| No log        | 3.45  | 200  | 16.0314         | 0.4669   | 0.4628 |
| No log        | 5.17  | 300  | 19.1999         | 0.4568   | 0.4479 |
| No log        | 6.9   | 400  | 21.8826         | 0.4546   | 0.4456 |
| 9.984         | 8.62  | 500  | 21.4137         | 0.4572   | 0.4573 |
| 9.984         | 10.34 | 600  | 23.3766         | 0.4396   | 0.4365 |
| 9.984         | 12.07 | 700  | 24.2726         | 0.4475   | 0.4365 |
| 9.984         | 13.79 | 800  | 24.3246         | 0.4502   | 0.4440 |
| 9.984         | 15.52 | 900  | 24.9899         | 0.4634   | 0.4616 |
| 1.9269        | 17.24 | 1000 | 24.6384         | 0.4616   | 0.4583 |
| 1.9269        | 18.97 | 1100 | 24.3379         | 0.4493   | 0.4454 |
| 1.9269        | 20.69 | 1200 | 24.6032         | 0.4625   | 0.4577 |
| 1.9269        | 22.41 | 1300 | 24.1732         | 0.4608   | 0.4572 |
| 1.9269        | 24.14 | 1400 | 25.5374         | 0.4493   | 0.4448 |
| 0.6962        | 25.86 | 1500 | 24.3690         | 0.4563   | 0.4553 |
| 0.6962        | 27.59 | 1600 | 24.9417         | 0.4515   | 0.4488 |
| 0.6962        | 29.31 | 1700 | 24.7382         | 0.4550   | 0.4534 |


### Framework versions

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