---
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-KD-SCR-PO-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-SCR-PO-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: 533.0406
- Accuracy: 0.3444
- F1: 0.2711

## 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: 8
- eval_batch_size: 32
- seed: 66
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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        | 1.7391  | 100  | 631.4247        | 0.3302   | 0.2694 |
| No log        | 3.4783  | 200  | 605.5723        | 0.3413   | 0.2651 |
| No log        | 5.2174  | 300  | 589.1194        | 0.3369   | 0.2521 |
| No log        | 6.9565  | 400  | 580.2668        | 0.3501   | 0.2633 |
| 574.1509      | 8.6957  | 500  | 571.8079        | 0.3254   | 0.2189 |
| 574.1509      | 10.4348 | 600  | 564.8586        | 0.3360   | 0.2072 |
| 574.1509      | 12.1739 | 700  | 559.2232        | 0.3417   | 0.2567 |
| 574.1509      | 13.9130 | 800  | 552.7770        | 0.3391   | 0.2289 |
| 574.1509      | 15.6522 | 900  | 549.6864        | 0.3333   | 0.2295 |
| 468.9151      | 17.3913 | 1000 | 545.1831        | 0.3338   | 0.2429 |
| 468.9151      | 19.1304 | 1100 | 541.3506        | 0.3466   | 0.2794 |
| 468.9151      | 20.8696 | 1200 | 538.9130        | 0.3355   | 0.2612 |
| 468.9151      | 22.6087 | 1300 | 537.2876        | 0.3470   | 0.2807 |
| 468.9151      | 24.3478 | 1400 | 535.7286        | 0.3426   | 0.2346 |
| 433.9469      | 26.0870 | 1500 | 533.7326        | 0.3492   | 0.2730 |
| 433.9469      | 27.8261 | 1600 | 533.2730        | 0.3338   | 0.2553 |
| 433.9469      | 29.5652 | 1700 | 533.0406        | 0.3444   | 0.2711 |


### Framework versions

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