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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_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
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