---
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_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-MSV-D2_data-cl-cardiff_cl_only55

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: 1.3677
- Accuracy: 0.4468
- F1: 0.4461

## 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        | 1.09  | 250  | 1.2834          | 0.4591   | 0.4503 |
| 1.2011        | 2.17  | 500  | 1.3504          | 0.4483   | 0.4403 |
| 1.2011        | 3.26  | 750  | 1.3205          | 0.4468   | 0.4415 |
| 1.0583        | 4.35  | 1000 | 1.3622          | 0.4406   | 0.4355 |
| 1.0583        | 5.43  | 1250 | 1.3754          | 0.4375   | 0.4333 |
| 0.9917        | 6.52  | 1500 | 1.3816          | 0.4398   | 0.4380 |
| 0.9917        | 7.61  | 1750 | 1.3783          | 0.4475   | 0.4434 |
| 0.9569        | 8.7   | 2000 | 1.3621          | 0.4529   | 0.4497 |
| 0.9569        | 9.78  | 2250 | 1.3658          | 0.4460   | 0.4450 |
| 0.939         | 10.87 | 2500 | 1.3567          | 0.4630   | 0.4616 |
| 0.939         | 11.96 | 2750 | 1.3631          | 0.4676   | 0.4675 |
| 0.9262        | 13.04 | 3000 | 1.3922          | 0.4421   | 0.4304 |
| 0.9262        | 14.13 | 3250 | 1.3950          | 0.4275   | 0.4135 |
| 0.9176        | 15.22 | 3500 | 1.3653          | 0.4660   | 0.4658 |
| 0.9176        | 16.3  | 3750 | 1.3690          | 0.4498   | 0.4449 |
| 0.9114        | 17.39 | 4000 | 1.3964          | 0.4398   | 0.4336 |
| 0.9114        | 18.48 | 4250 | 1.3738          | 0.4614   | 0.4600 |
| 0.9058        | 19.57 | 4500 | 1.3574          | 0.4730   | 0.4728 |
| 0.9058        | 20.65 | 4750 | 1.3716          | 0.4606   | 0.4577 |
| 0.9018        | 21.74 | 5000 | 1.3684          | 0.4583   | 0.4578 |
| 0.9018        | 22.83 | 5250 | 1.3791          | 0.4568   | 0.4534 |
| 0.8988        | 23.91 | 5500 | 1.3708          | 0.4560   | 0.4549 |
| 0.8988        | 25.0  | 5750 | 1.3438          | 0.4730   | 0.4728 |
| 0.8963        | 26.09 | 6000 | 1.3544          | 0.4622   | 0.4615 |
| 0.8963        | 27.17 | 6250 | 1.3508          | 0.4622   | 0.4590 |
| 0.8937        | 28.26 | 6500 | 1.3531          | 0.4637   | 0.4633 |
| 0.8937        | 29.35 | 6750 | 1.3677          | 0.4468   | 0.4461 |


### Framework versions

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