---
license: mit
base_model: haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-PR-CDF-EN-FROM-EN-D2_data-en-cardiff_eng_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-KD-PR-CDF-EN-FROM-EN-D2_data-en-cardiff_eng_only66

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: 1.3348
- Accuracy: 0.4846
- F1: 0.4848

## 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        | 1.72  | 100  | 1.3126          | 0.4718   | 0.4615 |
| No log        | 3.45  | 200  | 1.3334          | 0.4638   | 0.4466 |
| No log        | 5.17  | 300  | 1.3417          | 0.4810   | 0.4818 |
| No log        | 6.9   | 400  | 1.3541          | 0.4766   | 0.4702 |
| 1.1194        | 8.62  | 500  | 1.3613          | 0.4916   | 0.4913 |
| 1.1194        | 10.34 | 600  | 1.3438          | 0.4797   | 0.4784 |
| 1.1194        | 12.07 | 700  | 1.3501          | 0.4713   | 0.4713 |
| 1.1194        | 13.79 | 800  | 1.3617          | 0.4687   | 0.4683 |
| 1.1194        | 15.52 | 900  | 1.3527          | 0.4819   | 0.4812 |
| 0.9567        | 17.24 | 1000 | 1.3561          | 0.4824   | 0.4777 |
| 0.9567        | 18.97 | 1100 | 1.3531          | 0.4749   | 0.4732 |
| 0.9567        | 20.69 | 1200 | 1.3379          | 0.4960   | 0.4965 |
| 0.9567        | 22.41 | 1300 | 1.3384          | 0.4797   | 0.4793 |
| 0.9567        | 24.14 | 1400 | 1.3404          | 0.4824   | 0.4807 |
| 0.9355        | 25.86 | 1500 | 1.3475          | 0.4753   | 0.4755 |
| 0.9355        | 27.59 | 1600 | 1.3409          | 0.4780   | 0.4776 |
| 0.9355        | 29.31 | 1700 | 1.3348          | 0.4846   | 0.4848 |


### Framework versions

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