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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_alpha-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_alpha-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: 15.6158
- Accuracy: 0.4061
- F1: 0.3950
## 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: 2222
- 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 | 12.5428 | 0.3796 | 0.3146 |
| No log | 3.45 | 200 | 12.5657 | 0.3845 | 0.3414 |
| No log | 5.17 | 300 | 12.6557 | 0.3911 | 0.3631 |
| No log | 6.9 | 400 | 13.2594 | 0.4012 | 0.3807 |
| 13.0153 | 8.62 | 500 | 13.2352 | 0.3920 | 0.3836 |
| 13.0153 | 10.34 | 600 | 13.9522 | 0.3854 | 0.3638 |
| 13.0153 | 12.07 | 700 | 13.2917 | 0.3902 | 0.3891 |
| 13.0153 | 13.79 | 800 | 14.1281 | 0.3924 | 0.3931 |
| 13.0153 | 15.52 | 900 | 14.3501 | 0.4004 | 0.3889 |
| 9.1779 | 17.24 | 1000 | 14.2606 | 0.3955 | 0.3757 |
| 9.1779 | 18.97 | 1100 | 14.6113 | 0.4008 | 0.3953 |
| 9.1779 | 20.69 | 1200 | 14.9622 | 0.3973 | 0.3864 |
| 9.1779 | 22.41 | 1300 | 15.3755 | 0.3898 | 0.3652 |
| 9.1779 | 24.14 | 1400 | 15.1117 | 0.4087 | 0.4015 |
| 6.5007 | 25.86 | 1500 | 15.5084 | 0.4101 | 0.4075 |
| 6.5007 | 27.59 | 1600 | 15.5980 | 0.3955 | 0.3892 |
| 6.5007 | 29.31 | 1700 | 15.6158 | 0.4061 | 0.3950 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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