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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-CL-D2_data-cl-cardiff_cl_only_beta-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-CL-D2_data-cl-cardiff_cl_only_beta-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: 16.2119
- Accuracy: 0.3974
- F1: 0.3962
## 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: 6666
- 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 | 11.7960 | 0.3650 | 0.3427 |
| 13.5624 | 2.17 | 500 | 11.1810 | 0.3927 | 0.3922 |
| 13.5624 | 3.26 | 750 | 10.7353 | 0.3889 | 0.3725 |
| 11.0045 | 4.35 | 1000 | 11.0340 | 0.4113 | 0.4092 |
| 11.0045 | 5.43 | 1250 | 11.1511 | 0.3958 | 0.3764 |
| 9.4397 | 6.52 | 1500 | 11.3893 | 0.4128 | 0.4098 |
| 9.4397 | 7.61 | 1750 | 11.7867 | 0.4174 | 0.4136 |
| 8.0563 | 8.7 | 2000 | 12.7215 | 0.4020 | 0.3934 |
| 8.0563 | 9.78 | 2250 | 13.1991 | 0.4159 | 0.4158 |
| 7.071 | 10.87 | 2500 | 13.4791 | 0.3966 | 0.3938 |
| 7.071 | 11.96 | 2750 | 12.9321 | 0.4005 | 0.3939 |
| 5.9842 | 13.04 | 3000 | 13.5185 | 0.3873 | 0.3775 |
| 5.9842 | 14.13 | 3250 | 14.5623 | 0.4028 | 0.3984 |
| 5.0429 | 15.22 | 3500 | 14.7614 | 0.4012 | 0.3954 |
| 5.0429 | 16.3 | 3750 | 13.8500 | 0.4151 | 0.4149 |
| 4.4814 | 17.39 | 4000 | 14.0842 | 0.4051 | 0.4022 |
| 4.4814 | 18.48 | 4250 | 14.4055 | 0.3904 | 0.3804 |
| 4.0867 | 19.57 | 4500 | 15.5442 | 0.3858 | 0.3809 |
| 4.0867 | 20.65 | 4750 | 14.6236 | 0.3966 | 0.3951 |
| 3.5928 | 21.74 | 5000 | 14.9268 | 0.4005 | 0.3920 |
| 3.5928 | 22.83 | 5250 | 15.2065 | 0.3897 | 0.3884 |
| 3.2444 | 23.91 | 5500 | 16.5178 | 0.3889 | 0.3860 |
| 3.2444 | 25.0 | 5750 | 15.1592 | 0.3920 | 0.3879 |
| 3.0552 | 26.09 | 6000 | 15.4594 | 0.3974 | 0.3952 |
| 3.0552 | 27.17 | 6250 | 15.8492 | 0.3843 | 0.3842 |
| 2.8654 | 28.26 | 6500 | 15.8468 | 0.3827 | 0.3806 |
| 2.8654 | 29.35 | 6750 | 16.2119 | 0.3974 | 0.3962 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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