---
base_model: haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only
library_name: transformers
license: mit
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: scenario-NON-KD-PO-COPY-CDF-EN-D2_data-en-cardiff_eng_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-NON-KD-PO-COPY-CDF-EN-D2_data-en-cardiff_eng_only55

This model is a fine-tuned version of [haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only](https://huggingface.co/haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 5.0783
- Accuracy: 0.4696
- F1: 0.4675

## 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        | 1.7241  | 100  | 1.2348          | 0.4608   | 0.4572 |
| No log        | 3.4483  | 200  | 1.4918          | 0.4828   | 0.4811 |
| No log        | 5.1724  | 300  | 1.6208          | 0.4890   | 0.4892 |
| No log        | 6.8966  | 400  | 2.2442          | 0.4757   | 0.4744 |
| 0.5368        | 8.6207  | 500  | 2.8887          | 0.4828   | 0.4780 |
| 0.5368        | 10.3448 | 600  | 3.2901          | 0.4643   | 0.4608 |
| 0.5368        | 12.0690 | 700  | 3.5079          | 0.4630   | 0.4577 |
| 0.5368        | 13.7931 | 800  | 3.9045          | 0.4771   | 0.4771 |
| 0.5368        | 15.5172 | 900  | 4.0691          | 0.4586   | 0.4537 |
| 0.0674        | 17.2414 | 1000 | 4.3815          | 0.4718   | 0.4709 |
| 0.0674        | 18.9655 | 1100 | 4.5190          | 0.4674   | 0.4660 |
| 0.0674        | 20.6897 | 1200 | 4.7439          | 0.4656   | 0.4637 |
| 0.0674        | 22.4138 | 1300 | 4.9470          | 0.4678   | 0.4650 |
| 0.0674        | 24.1379 | 1400 | 4.9131          | 0.4727   | 0.4725 |
| 0.0123        | 25.8621 | 1500 | 4.9607          | 0.4793   | 0.4788 |
| 0.0123        | 27.5862 | 1600 | 4.9727          | 0.4784   | 0.4783 |
| 0.0123        | 29.3103 | 1700 | 5.0783          | 0.4696   | 0.4675 |


### Framework versions

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