---
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-PR-CDF-EN-FROM-EN-D2_data-en-cardiff_eng_only44
  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-PR-CDF-EN-FROM-EN-D2_data-en-cardiff_eng_only44

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: 1.3472
- Accuracy: 0.4854
- F1: 0.4837

## 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: 44
- 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  | 1.2889          | 0.4594   | 0.4362 |
| No log        | 3.45  | 200  | 1.2863          | 0.4802   | 0.4774 |
| No log        | 5.17  | 300  | 1.3275          | 0.4612   | 0.4493 |
| No log        | 6.9   | 400  | 1.3428          | 0.4885   | 0.4874 |
| 1.1183        | 8.62  | 500  | 1.3395          | 0.4841   | 0.4835 |
| 1.1183        | 10.34 | 600  | 1.3621          | 0.4705   | 0.4689 |
| 1.1183        | 12.07 | 700  | 1.3524          | 0.4643   | 0.4624 |
| 1.1183        | 13.79 | 800  | 1.3665          | 0.4660   | 0.4617 |
| 1.1183        | 15.52 | 900  | 1.3531          | 0.4793   | 0.4762 |
| 0.9576        | 17.24 | 1000 | 1.3762          | 0.4669   | 0.4633 |
| 0.9576        | 18.97 | 1100 | 1.3615          | 0.4718   | 0.4681 |
| 0.9576        | 20.69 | 1200 | 1.3656          | 0.4691   | 0.4638 |
| 0.9576        | 22.41 | 1300 | 1.3684          | 0.4722   | 0.4685 |
| 0.9576        | 24.14 | 1400 | 1.3559          | 0.4740   | 0.4741 |
| 0.9369        | 25.86 | 1500 | 1.3527          | 0.4753   | 0.4739 |
| 0.9369        | 27.59 | 1600 | 1.3407          | 0.4762   | 0.4757 |
| 0.9369        | 29.31 | 1700 | 1.3472          | 0.4854   | 0.4837 |


### Framework versions

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