---
license: mit
base_model: haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-PR-CDF-EN-FROM-CL-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-KD-PR-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only55

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: 1.3279
- Accuracy: 0.4881
- F1: 0.4855

## 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        | 1.72  | 100  | 1.3136          | 0.4599   | 0.4267 |
| No log        | 3.45  | 200  | 1.4057          | 0.4506   | 0.4056 |
| No log        | 5.17  | 300  | 1.3382          | 0.4797   | 0.4752 |
| No log        | 6.9   | 400  | 1.3472          | 0.4890   | 0.4858 |
| 1.1235        | 8.62  | 500  | 1.3400          | 0.4863   | 0.4865 |
| 1.1235        | 10.34 | 600  | 1.3593          | 0.4837   | 0.4776 |
| 1.1235        | 12.07 | 700  | 1.3787          | 0.4638   | 0.4526 |
| 1.1235        | 13.79 | 800  | 1.3508          | 0.4868   | 0.4853 |
| 1.1235        | 15.52 | 900  | 1.3393          | 0.4912   | 0.4895 |
| 0.9596        | 17.24 | 1000 | 1.3570          | 0.4802   | 0.4693 |
| 0.9596        | 18.97 | 1100 | 1.3359          | 0.4929   | 0.4905 |
| 0.9596        | 20.69 | 1200 | 1.3386          | 0.4846   | 0.4816 |
| 0.9596        | 22.41 | 1300 | 1.3372          | 0.4916   | 0.4903 |
| 0.9596        | 24.14 | 1400 | 1.3271          | 0.4956   | 0.4932 |
| 0.9384        | 25.86 | 1500 | 1.3313          | 0.4921   | 0.4913 |
| 0.9384        | 27.59 | 1600 | 1.3341          | 0.4907   | 0.4897 |
| 0.9384        | 29.31 | 1700 | 1.3279          | 0.4881   | 0.4855 |


### Framework versions

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