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---
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_only66
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_only66
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: 1.3328
- Accuracy: 0.4881
- F1: 0.4886
## 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: 66
- 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 | 1.3021 | 0.4947 | 0.4907 |
| No log | 3.45 | 200 | 1.3343 | 0.4713 | 0.4544 |
| No log | 5.17 | 300 | 1.3753 | 0.4899 | 0.4851 |
| No log | 6.9 | 400 | 1.3847 | 0.4572 | 0.4442 |
| 1.1115 | 8.62 | 500 | 1.3543 | 0.4757 | 0.4743 |
| 1.1115 | 10.34 | 600 | 1.3693 | 0.4691 | 0.4612 |
| 1.1115 | 12.07 | 700 | 1.3906 | 0.4687 | 0.4600 |
| 1.1115 | 13.79 | 800 | 1.3669 | 0.4700 | 0.4635 |
| 1.1115 | 15.52 | 900 | 1.3459 | 0.4899 | 0.4892 |
| 0.9572 | 17.24 | 1000 | 1.3562 | 0.4912 | 0.4872 |
| 0.9572 | 18.97 | 1100 | 1.3492 | 0.4846 | 0.4842 |
| 0.9572 | 20.69 | 1200 | 1.3918 | 0.4660 | 0.4504 |
| 0.9572 | 22.41 | 1300 | 1.3279 | 0.4960 | 0.4932 |
| 0.9572 | 24.14 | 1400 | 1.3440 | 0.4832 | 0.4832 |
| 0.936 | 25.86 | 1500 | 1.3460 | 0.4863 | 0.4863 |
| 0.936 | 27.59 | 1600 | 1.3371 | 0.4907 | 0.4909 |
| 0.936 | 29.31 | 1700 | 1.3328 | 0.4881 | 0.4886 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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