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---
license: mit
base_model: haryoaw/scenario-TCR_data-en-cardiff_eng_only2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-PO-CDF-EN-FROM-EN-D2_data-en-cardiff_eng_only_gamma-jason
results: []
---
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# scenario-KD-PO-CDF-EN-FROM-EN-D2_data-en-cardiff_eng_only_gamma-jason
This model is a fine-tuned version of [haryoaw/scenario-TCR_data-en-cardiff_eng_only2](https://huggingface.co/haryoaw/scenario-TCR_data-en-cardiff_eng_only2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 26.1249
- Accuracy: 0.3880
- F1: 0.3851
## 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: 88458
- 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 | 21.3705 | 0.3571 | 0.3491 |
| No log | 3.45 | 200 | 21.4480 | 0.3726 | 0.3483 |
| No log | 5.17 | 300 | 22.0203 | 0.3796 | 0.3543 |
| No log | 6.9 | 400 | 21.4652 | 0.3955 | 0.3889 |
| 21.8455 | 8.62 | 500 | 22.0346 | 0.4105 | 0.4068 |
| 21.8455 | 10.34 | 600 | 22.5203 | 0.4158 | 0.4064 |
| 21.8455 | 12.07 | 700 | 22.5508 | 0.3951 | 0.3893 |
| 21.8455 | 13.79 | 800 | 23.1432 | 0.3889 | 0.3760 |
| 21.8455 | 15.52 | 900 | 23.8503 | 0.3946 | 0.3841 |
| 15.7725 | 17.24 | 1000 | 24.0330 | 0.3964 | 0.3792 |
| 15.7725 | 18.97 | 1100 | 24.0211 | 0.4101 | 0.4097 |
| 15.7725 | 20.69 | 1200 | 25.0036 | 0.3973 | 0.3846 |
| 15.7725 | 22.41 | 1300 | 25.3511 | 0.3955 | 0.3880 |
| 15.7725 | 24.14 | 1400 | 25.6258 | 0.3867 | 0.3765 |
| 11.4934 | 25.86 | 1500 | 25.5123 | 0.3920 | 0.3904 |
| 11.4934 | 27.59 | 1600 | 25.4662 | 0.4021 | 0.3990 |
| 11.4934 | 29.31 | 1700 | 26.1249 | 0.3880 | 0.3851 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3