---
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_only55
  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_only55

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: 1.3581
- Accuracy: 0.4652
- F1: 0.4628

## 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: 55
- 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  | 1.3031          | 0.4771   | 0.4716 |
| No log        | 3.45  | 200  | 1.3400          | 0.4683   | 0.4652 |
| No log        | 5.17  | 300  | 1.3825          | 0.4519   | 0.4469 |
| No log        | 6.9   | 400  | 1.3630          | 0.4506   | 0.4420 |
| 1.1126        | 8.62  | 500  | 1.3707          | 0.4638   | 0.4582 |
| 1.1126        | 10.34 | 600  | 1.3829          | 0.4586   | 0.4484 |
| 1.1126        | 12.07 | 700  | 1.3900          | 0.4515   | 0.4453 |
| 1.1126        | 13.79 | 800  | 1.3686          | 0.4533   | 0.4524 |
| 1.1126        | 15.52 | 900  | 1.3663          | 0.4691   | 0.4671 |
| 0.9617        | 17.24 | 1000 | 1.3568          | 0.4634   | 0.4633 |
| 0.9617        | 18.97 | 1100 | 1.3790          | 0.4687   | 0.4636 |
| 0.9617        | 20.69 | 1200 | 1.3537          | 0.4744   | 0.4719 |
| 0.9617        | 22.41 | 1300 | 1.3759          | 0.4735   | 0.4682 |
| 0.9617        | 24.14 | 1400 | 1.3573          | 0.4687   | 0.4675 |
| 0.9417        | 25.86 | 1500 | 1.3581          | 0.4740   | 0.4734 |
| 0.9417        | 27.59 | 1600 | 1.3547          | 0.4608   | 0.4588 |
| 0.9417        | 29.31 | 1700 | 1.3581          | 0.4652   | 0.4628 |


### Framework versions

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