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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-PO-CDF-CL-D2_data-cl-cardiff_cl_only44
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-CL-D2_data-cl-cardiff_cl_only44
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: 35.0455
- Accuracy: 0.4421
- F1: 0.4372
## 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: 44
- 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 | 22.7040 | 0.4236 | 0.4110 |
| 23.1676 | 2.17 | 500 | 21.6418 | 0.4336 | 0.4116 |
| 23.1676 | 3.26 | 750 | 24.6174 | 0.4267 | 0.4155 |
| 12.9705 | 4.35 | 1000 | 27.2959 | 0.4460 | 0.4447 |
| 12.9705 | 5.43 | 1250 | 28.1257 | 0.4375 | 0.4315 |
| 7.1171 | 6.52 | 1500 | 27.9161 | 0.4360 | 0.4279 |
| 7.1171 | 7.61 | 1750 | 29.9352 | 0.4383 | 0.4361 |
| 4.3718 | 8.7 | 2000 | 34.5593 | 0.4298 | 0.4191 |
| 4.3718 | 9.78 | 2250 | 34.0346 | 0.4421 | 0.4373 |
| 3.4048 | 10.87 | 2500 | 33.3230 | 0.4390 | 0.4351 |
| 3.4048 | 11.96 | 2750 | 35.1604 | 0.4367 | 0.4313 |
| 2.4739 | 13.04 | 3000 | 33.4441 | 0.4228 | 0.4170 |
| 2.4739 | 14.13 | 3250 | 32.9534 | 0.4367 | 0.4308 |
| 2.0055 | 15.22 | 3500 | 34.2647 | 0.4429 | 0.4414 |
| 2.0055 | 16.3 | 3750 | 33.4915 | 0.4460 | 0.4450 |
| 1.4812 | 17.39 | 4000 | 35.4776 | 0.4298 | 0.4249 |
| 1.4812 | 18.48 | 4250 | 35.4540 | 0.4375 | 0.4366 |
| 1.299 | 19.57 | 4500 | 34.2270 | 0.4468 | 0.4467 |
| 1.299 | 20.65 | 4750 | 34.7234 | 0.4460 | 0.4441 |
| 0.98 | 21.74 | 5000 | 34.8872 | 0.4352 | 0.4294 |
| 0.98 | 22.83 | 5250 | 34.8777 | 0.4383 | 0.4370 |
| 0.7847 | 23.91 | 5500 | 35.0968 | 0.4522 | 0.4518 |
| 0.7847 | 25.0 | 5750 | 34.3877 | 0.4329 | 0.4285 |
| 0.6835 | 26.09 | 6000 | 35.0458 | 0.4390 | 0.4365 |
| 0.6835 | 27.17 | 6250 | 35.2727 | 0.4360 | 0.4326 |
| 0.5378 | 28.26 | 6500 | 33.4029 | 0.4390 | 0.4353 |
| 0.5378 | 29.35 | 6750 | 35.0455 | 0.4421 | 0.4372 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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