---
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-PO-CDF-EN-FROM-CL-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-PO-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only44

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: 39.7248
- Accuracy: 0.4511
- F1: 0.4490

## 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  | 25.4567         | 0.4422   | 0.4387 |
| No log        | 3.45  | 200  | 25.1633         | 0.4793   | 0.4777 |
| No log        | 5.17  | 300  | 30.1100         | 0.4356   | 0.4168 |
| No log        | 6.9   | 400  | 30.5006         | 0.4815   | 0.4818 |
| 16.9844       | 8.62  | 500  | 32.4822         | 0.4493   | 0.4441 |
| 16.9844       | 10.34 | 600  | 35.6753         | 0.4541   | 0.4525 |
| 16.9844       | 12.07 | 700  | 37.9029         | 0.4669   | 0.4628 |
| 16.9844       | 13.79 | 800  | 40.5685         | 0.4462   | 0.4400 |
| 16.9844       | 15.52 | 900  | 39.8826         | 0.4489   | 0.4407 |
| 3.5242        | 17.24 | 1000 | 42.5352         | 0.4325   | 0.4211 |
| 3.5242        | 18.97 | 1100 | 36.9882         | 0.4696   | 0.4686 |
| 3.5242        | 20.69 | 1200 | 39.5527         | 0.4519   | 0.4478 |
| 3.5242        | 22.41 | 1300 | 40.9362         | 0.4295   | 0.4201 |
| 3.5242        | 24.14 | 1400 | 40.2929         | 0.4471   | 0.4446 |
| 1.4703        | 25.86 | 1500 | 39.7746         | 0.4568   | 0.4509 |
| 1.4703        | 27.59 | 1600 | 39.0260         | 0.4524   | 0.4503 |
| 1.4703        | 29.31 | 1700 | 39.7248         | 0.4511   | 0.4490 |


### Framework versions

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