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---
license: mit
base_model: haryoaw/scenario-TCR_data-cl-cardiff_cl_only2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-PO-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only_delta-jason
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-PO-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only_delta-jason
This model is a fine-tuned version of [haryoaw/scenario-TCR_data-cl-cardiff_cl_only2](https://huggingface.co/haryoaw/scenario-TCR_data-cl-cardiff_cl_only2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 16.2614
- Accuracy: 0.3911
- F1: 0.3741
## 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: 7777
- 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 | 12.7454 | 0.3338 | 0.1921 |
| No log | 3.45 | 200 | 12.5764 | 0.3792 | 0.3477 |
| No log | 5.17 | 300 | 12.7859 | 0.3911 | 0.3622 |
| No log | 6.9 | 400 | 12.6337 | 0.3955 | 0.3966 |
| 12.945 | 8.62 | 500 | 13.0332 | 0.3920 | 0.3842 |
| 12.945 | 10.34 | 600 | 13.7887 | 0.3955 | 0.3882 |
| 12.945 | 12.07 | 700 | 14.4400 | 0.3924 | 0.3773 |
| 12.945 | 13.79 | 800 | 15.9912 | 0.3805 | 0.3378 |
| 12.945 | 15.52 | 900 | 15.2262 | 0.3902 | 0.3688 |
| 8.3121 | 17.24 | 1000 | 14.6109 | 0.3968 | 0.3856 |
| 8.3121 | 18.97 | 1100 | 15.0076 | 0.3990 | 0.3777 |
| 8.3121 | 20.69 | 1200 | 15.1415 | 0.4012 | 0.3918 |
| 8.3121 | 22.41 | 1300 | 15.4897 | 0.4096 | 0.3931 |
| 8.3121 | 24.14 | 1400 | 16.0139 | 0.4021 | 0.3922 |
| 5.8446 | 25.86 | 1500 | 15.8831 | 0.4008 | 0.3849 |
| 5.8446 | 27.59 | 1600 | 16.0754 | 0.3915 | 0.3708 |
| 5.8446 | 29.31 | 1700 | 16.2614 | 0.3911 | 0.3741 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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