---
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-MSV-D2_data-cl-cardiff_cl_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-MSV-D2_data-cl-cardiff_cl_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: 1.3590
- Accuracy: 0.4630
- 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: 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        | 1.09  | 250  | 1.3195          | 0.4390   | 0.4186 |
| 1.1991        | 2.17  | 500  | 1.2866          | 0.4537   | 0.4542 |
| 1.1991        | 3.26  | 750  | 1.3622          | 0.4383   | 0.4293 |
| 1.0569        | 4.35  | 1000 | 1.3662          | 0.4252   | 0.4155 |
| 1.0569        | 5.43  | 1250 | 1.3920          | 0.4275   | 0.4229 |
| 0.9882        | 6.52  | 1500 | 1.3607          | 0.4560   | 0.4549 |
| 0.9882        | 7.61  | 1750 | 1.3742          | 0.4468   | 0.4429 |
| 0.9542        | 8.7   | 2000 | 1.4048          | 0.4329   | 0.4284 |
| 0.9542        | 9.78  | 2250 | 1.3944          | 0.4344   | 0.4227 |
| 0.9374        | 10.87 | 2500 | 1.3725          | 0.4414   | 0.4417 |
| 0.9374        | 11.96 | 2750 | 1.3790          | 0.4491   | 0.4464 |
| 0.9261        | 13.04 | 3000 | 1.3687          | 0.4552   | 0.4510 |
| 0.9261        | 14.13 | 3250 | 1.3778          | 0.4475   | 0.4438 |
| 0.9164        | 15.22 | 3500 | 1.3888          | 0.4583   | 0.4554 |
| 0.9164        | 16.3  | 3750 | 1.3785          | 0.4498   | 0.4415 |
| 0.9101        | 17.39 | 4000 | 1.3778          | 0.4568   | 0.4530 |
| 0.9101        | 18.48 | 4250 | 1.4075          | 0.4398   | 0.4261 |
| 0.9053        | 19.57 | 4500 | 1.3610          | 0.4576   | 0.4575 |
| 0.9053        | 20.65 | 4750 | 1.3679          | 0.4568   | 0.4570 |
| 0.9026        | 21.74 | 5000 | 1.3653          | 0.4614   | 0.4617 |
| 0.9026        | 22.83 | 5250 | 1.3701          | 0.4468   | 0.4465 |
| 0.8977        | 23.91 | 5500 | 1.3753          | 0.4498   | 0.4475 |
| 0.8977        | 25.0  | 5750 | 1.3781          | 0.4545   | 0.4532 |
| 0.8953        | 26.09 | 6000 | 1.3811          | 0.4468   | 0.4455 |
| 0.8953        | 27.17 | 6250 | 1.3609          | 0.4545   | 0.4527 |
| 0.893         | 28.26 | 6500 | 1.3696          | 0.4452   | 0.4433 |
| 0.893         | 29.35 | 6750 | 1.3590          | 0.4630   | 0.4628 |


### Framework versions

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