---
library_name: transformers
license: mit
base_model: haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
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: 5.0027
- Accuracy: 0.4656
- F1: 0.4619

## 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  | 1.2748          | 0.4339   | 0.4142 |
| No log        | 3.4483  | 200  | 1.3406          | 0.4660   | 0.4596 |
| No log        | 5.1724  | 300  | 1.5563          | 0.4757   | 0.4694 |
| No log        | 6.8966  | 400  | 2.0113          | 0.4683   | 0.4688 |
| 0.5741        | 8.6207  | 500  | 2.4441          | 0.4700   | 0.4666 |
| 0.5741        | 10.3448 | 600  | 2.6979          | 0.4656   | 0.4657 |
| 0.5741        | 12.0690 | 700  | 3.3013          | 0.4630   | 0.4595 |
| 0.5741        | 13.7931 | 800  | 3.6311          | 0.4652   | 0.4630 |
| 0.5741        | 15.5172 | 900  | 4.2150          | 0.4537   | 0.4431 |
| 0.0798        | 17.2414 | 1000 | 4.2688          | 0.4581   | 0.4507 |
| 0.0798        | 18.9655 | 1100 | 4.4930          | 0.4630   | 0.4597 |
| 0.0798        | 20.6897 | 1200 | 4.8125          | 0.4537   | 0.4398 |
| 0.0798        | 22.4138 | 1300 | 4.7923          | 0.4674   | 0.4603 |
| 0.0798        | 24.1379 | 1400 | 4.8840          | 0.4616   | 0.4594 |
| 0.0132        | 25.8621 | 1500 | 5.0249          | 0.4612   | 0.4539 |
| 0.0132        | 27.5862 | 1600 | 5.0564          | 0.4594   | 0.4534 |
| 0.0132        | 29.3103 | 1700 | 5.0027          | 0.4656   | 0.4619 |


### Framework versions

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