---
license: mit
base_model: haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-PR-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only66
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# scenario-KD-PR-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only66

This model is a fine-tuned version of [haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only](https://huggingface.co/haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3328
- Accuracy: 0.4881
- F1: 0.4886

## 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  | 1.3021          | 0.4947   | 0.4907 |
| No log        | 3.45  | 200  | 1.3343          | 0.4713   | 0.4544 |
| No log        | 5.17  | 300  | 1.3753          | 0.4899   | 0.4851 |
| No log        | 6.9   | 400  | 1.3847          | 0.4572   | 0.4442 |
| 1.1115        | 8.62  | 500  | 1.3543          | 0.4757   | 0.4743 |
| 1.1115        | 10.34 | 600  | 1.3693          | 0.4691   | 0.4612 |
| 1.1115        | 12.07 | 700  | 1.3906          | 0.4687   | 0.4600 |
| 1.1115        | 13.79 | 800  | 1.3669          | 0.4700   | 0.4635 |
| 1.1115        | 15.52 | 900  | 1.3459          | 0.4899   | 0.4892 |
| 0.9572        | 17.24 | 1000 | 1.3562          | 0.4912   | 0.4872 |
| 0.9572        | 18.97 | 1100 | 1.3492          | 0.4846   | 0.4842 |
| 0.9572        | 20.69 | 1200 | 1.3918          | 0.4660   | 0.4504 |
| 0.9572        | 22.41 | 1300 | 1.3279          | 0.4960   | 0.4932 |
| 0.9572        | 24.14 | 1400 | 1.3440          | 0.4832   | 0.4832 |
| 0.936         | 25.86 | 1500 | 1.3460          | 0.4863   | 0.4863 |
| 0.936         | 27.59 | 1600 | 1.3371          | 0.4907   | 0.4909 |
| 0.936         | 29.31 | 1700 | 1.3328          | 0.4881   | 0.4886 |


### Framework versions

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