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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-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_gamma
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-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_gamma
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: 5.6776
- Accuracy: 0.4560
- F1: 0.4557
## 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: 11423
- 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 | 1.09 | 250 | 1.7114 | 0.4745 | 0.4746 |
| 0.5344 | 2.17 | 500 | 2.4454 | 0.4522 | 0.4441 |
| 0.5344 | 3.26 | 750 | 2.7492 | 0.4699 | 0.4693 |
| 0.2322 | 4.35 | 1000 | 3.0156 | 0.4336 | 0.4123 |
| 0.2322 | 5.43 | 1250 | 2.9947 | 0.4799 | 0.4819 |
| 0.1279 | 6.52 | 1500 | 3.7528 | 0.4506 | 0.4474 |
| 0.1279 | 7.61 | 1750 | 3.5806 | 0.4560 | 0.4560 |
| 0.0973 | 8.7 | 2000 | 3.8704 | 0.4545 | 0.4510 |
| 0.0973 | 9.78 | 2250 | 4.0113 | 0.4498 | 0.4450 |
| 0.0683 | 10.87 | 2500 | 3.5910 | 0.4676 | 0.4690 |
| 0.0683 | 11.96 | 2750 | 4.3665 | 0.4506 | 0.4480 |
| 0.0498 | 13.04 | 3000 | 4.2188 | 0.4799 | 0.4809 |
| 0.0498 | 14.13 | 3250 | 4.8550 | 0.4398 | 0.4315 |
| 0.0324 | 15.22 | 3500 | 4.7206 | 0.4630 | 0.4586 |
| 0.0324 | 16.3 | 3750 | 5.0101 | 0.4444 | 0.4392 |
| 0.025 | 17.39 | 4000 | 5.0926 | 0.4660 | 0.4667 |
| 0.025 | 18.48 | 4250 | 4.8167 | 0.4869 | 0.4886 |
| 0.0248 | 19.57 | 4500 | 5.1087 | 0.4606 | 0.4610 |
| 0.0248 | 20.65 | 4750 | 5.4661 | 0.4429 | 0.4365 |
| 0.0154 | 21.74 | 5000 | 5.2199 | 0.4730 | 0.4742 |
| 0.0154 | 22.83 | 5250 | 5.1442 | 0.4807 | 0.4825 |
| 0.0112 | 23.91 | 5500 | 5.4588 | 0.4691 | 0.4696 |
| 0.0112 | 25.0 | 5750 | 5.4026 | 0.4653 | 0.4654 |
| 0.0112 | 26.09 | 6000 | 5.6362 | 0.4506 | 0.4466 |
| 0.0112 | 27.17 | 6250 | 5.5405 | 0.4614 | 0.4620 |
| 0.0046 | 28.26 | 6500 | 5.6038 | 0.4591 | 0.4590 |
| 0.0046 | 29.35 | 6750 | 5.6776 | 0.4560 | 0.4557 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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