---
base_model: haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only
library_name: transformers
license: mit
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only66
  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-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_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: 5.9979
- Accuracy: 0.4498
- F1: 0.4497

## 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        | 1.0870  | 250  | 1.2493          | 0.4568   | 0.4501 |
| 0.812         | 2.1739  | 500  | 1.5854          | 0.4637   | 0.4628 |
| 0.812         | 3.2609  | 750  | 1.8772          | 0.4614   | 0.4605 |
| 0.4271        | 4.3478  | 1000 | 2.3694          | 0.4414   | 0.4339 |
| 0.4271        | 5.4348  | 1250 | 2.6689          | 0.4537   | 0.4473 |
| 0.1992        | 6.5217  | 1500 | 3.0050          | 0.4537   | 0.4527 |
| 0.1992        | 7.6087  | 1750 | 3.1201          | 0.4468   | 0.4406 |
| 0.1147        | 8.6957  | 2000 | 3.9025          | 0.4360   | 0.4298 |
| 0.1147        | 9.7826  | 2250 | 4.0949          | 0.4390   | 0.4331 |
| 0.0816        | 10.8696 | 2500 | 4.3006          | 0.4306   | 0.4218 |
| 0.0816        | 11.9565 | 2750 | 4.5881          | 0.4606   | 0.4569 |
| 0.0558        | 13.0435 | 3000 | 4.4255          | 0.4576   | 0.4577 |
| 0.0558        | 14.1304 | 3250 | 5.1150          | 0.4606   | 0.4600 |
| 0.0388        | 15.2174 | 3500 | 4.6378          | 0.4568   | 0.4571 |
| 0.0388        | 16.3043 | 3750 | 5.2331          | 0.4498   | 0.4458 |
| 0.0269        | 17.3913 | 4000 | 5.3200          | 0.4491   | 0.4481 |
| 0.0269        | 18.4783 | 4250 | 5.2543          | 0.4599   | 0.4583 |
| 0.0175        | 19.5652 | 4500 | 5.3747          | 0.4552   | 0.4548 |
| 0.0175        | 20.6522 | 4750 | 5.4521          | 0.4460   | 0.4448 |
| 0.0181        | 21.7391 | 5000 | 5.3489          | 0.4606   | 0.4604 |
| 0.0181        | 22.8261 | 5250 | 5.8017          | 0.4552   | 0.4543 |
| 0.0093        | 23.9130 | 5500 | 5.6669          | 0.4560   | 0.4560 |
| 0.0093        | 25.0    | 5750 | 5.5959          | 0.4529   | 0.4517 |
| 0.0076        | 26.0870 | 6000 | 5.8141          | 0.4576   | 0.4554 |
| 0.0076        | 27.1739 | 6250 | 5.8656          | 0.4560   | 0.4556 |
| 0.006         | 28.2609 | 6500 | 5.9365          | 0.4583   | 0.4577 |
| 0.006         | 29.3478 | 6750 | 5.9979          | 0.4498   | 0.4497 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.19.1